Healthcare Data Engineering

Healthcare Data Engineering Jobs

7 jobs found

1d ago

Analytics Engineer

ELYON International Washington, DC

Washington, DC

1d ago

$55 - $60/hr Full time Azure Business Intelligence Data Analytics

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Job Description

ELYON International is seeking an Analytics Engineer to support a large-scale federal healthcare data and technology modernization program. In this onsite role in Washington, DC, you will bridge data engineering and analytics by transforming complex inputs into reliable, analytics-ready datasets used for reporting, dashboards, and operational analysis.

You will be responsible for building scalable analytics data models and transformation pipelines, with an emphasis on data quality, testing, monitoring, and performance. The work will support enterprise reporting solutions and help stakeholders make data-driven decisions across a complex environment.

Responsibilities

Design, develop, and maintain scalable analytics data models and transformation pipelines.
Transform raw data into trusted, structured, analytics-ready datasets.
Create reusable data models and curated datasets to support reporting, dashboards, analytics, and operational decision-making.
Write and optimize complex SQL queries for large-scale datasets.
Develop automated data transformation and validation processes.
Establish data quality checks, testing practices, and monitoring processes.
Partner with data engineers to optimize data ingestion, transformation, and storage processes.
Collaborate with analysts and business stakeholders to understand reporting requirements and translate them into scalable technical solutions.
Support business intelligence dashboards and enterprise reporting solutions.
Maintain documentation for data models, transformations, lineage, and business logic.
Identify and resolve data quality, consistency, and performance issues.
Contribute to enterprise data governance, metadata management, and data standardization efforts.
Participate in Agile development activities, technical reviews, and release planning.
Support cloud-based data modernization and analytics initiatives.

Requirements

Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, Statistics, or a related technical discipline.
5+ years of experience working in analytics engineering, data engineering, business intelligence engineering, or a related data-focused role.
Advanced proficiency with SQL and relational data concepts.
Experience developing data models and data transformation pipelines.
Experience working with modern data warehouses, cloud data platforms, or data lake environments.
Strong understanding of ETL/ELT concepts and data integration.
Experience implementing data quality validation and testing.
Experience with Python or another data-oriented programming language.
Experience with version control and modern software development practices.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent communication skills and the ability to collaborate with both technical and business stakeholders.
Ability to meet applicable federal background investigation requirements.

Technologies

SQL, Python, dbt (Data Build Tool), Snowflake, Databricks
Microsoft Azure, AWS
Power BI, Tableau, Looker
HL7, FHIR

Benefits

Paid sick leave
Medical/Dental (optional)
401(k) Retirement Plan (optional)
Employer Paid Life Insurance
Employer Paid Short Term Disability
Optional Life Insurance

Preferred Qualifications

Previous experience supporting federal healthcare, health IT, or large federal data programs.
Experience working with healthcare or clinical data environments.
Experience with dbt (Data Build Tool).
Experience with Snowflake, Databricks, Microsoft Azure, AWS, or equivalent cloud data platforms.
Experience with modern BI platforms such as Power BI, Tableau, or Looker.
Experience with data cataloging, lineage, metadata management, and governance.
Familiarity with healthcare interoperability standards such as HL7 or FHIR.
Experience working within Agile and DevSecOps environments.

Compensation: USD 55–60 per hour. This position is contingent upon ELYON’s receipt of contract award, Government acceptance of the proposed candidate, completion of required onboarding, and continued contract funding. In addition, solutions must comply with applicable federal security, privacy, governance, and data management requirements.

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2d ago

Senior Data Engineer

VeeRteq Solutions Inc. Irving, TX

Irving, TX

2d ago

Full time Senior Big Data Bigdata

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Job Description

VeeRteq Solutions Inc. is hiring a Senior Data Engineer to support healthcare data platforms. The role focuses on designing and maintaining scalable, GCP-based ETL/ELT pipelines and lakehouse solutions, with hands-on work across core data engineering and healthcare data domains.

Role Overview

You will build and improve healthcare data pipelines on Google Cloud Platform, ensuring reliable data delivery and strong data quality. Work includes developing and optimizing ETL/ELT workflows, lakehouse components, and production support activities. The position also involves integrating healthcare data through common ingestion patterns and collaborating across technical and business teams.

Responsibilities

Design, develop, and support scalable data pipelines and healthcare data platforms on GCP.
Build and optimize ETL/ELT pipelines using PySpark, dbt, Dataproc, and Data Composer.
Develop and maintain data solutions using BigQuery, BigLake, Apache Iceberg, and Starburst.
Implement healthcare data integrations using APIs, SFTP, and Kafka.
Design scalable data models and ensure data quality, reliability, and performance.
Perform data validation, troubleshooting, and performance optimization across data platforms.
Support production deployments, including monitoring, troubleshooting, and issue resolution.
Implement and maintain data governance, security, and data management best practices.
Collaborate with architects, data analysts, business stakeholders, and engineering teams.
Support healthcare data integration and data quality initiatives.
Contribute to modern lakehouse architecture and large-scale distributed data processing.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, Data Engineering, Data Science, or a related field.
8+ years of experience in Data Engineering and Cloud Data Platforms.
Strong hands-on experience with Google Cloud Platform (GCP).
Experience building and supporting large-scale healthcare data platforms.
Experience working with one or more healthcare data domains: Claims, Member, Provider, or Clinical data.
Understanding of healthcare data integration, healthcare data quality, data governance, healthcare data management, and healthcare data security practices.

Technologies

Google Cloud Platform (GCP), Dataproc, Data Composer, BigQuery, BigLake, Apache Iceberg, Starburst, dbt, PySpark, SQL, ETL/ELT, Kafka, APIs, SFTP.

Mandatory Technical Skills

GCP
BigQuery
BigLake
Dataproc
Data Composer
Apache Iceberg
Starburst
dbt
PySpark
SQL
ETL/ELT
Kafka
API Integrations
SFTP
Data Modeling
Performance Optimization
Production Monitoring & Troubleshooting

Preferred Qualifications

Experience with healthcare interoperability standards such as FHIR, HL7, or EDI.
GCP or other relevant cloud certifications.
Experience with cloud-native data platforms.
Experience working in Agile/Scrum delivery environments.
Experience with modern lakehouse architectures and open table formats.
Experience with cloud-native monitoring and observability.
Experience implementing automated data quality practices.
Experience optimizing large-scale distributed processing and analytical workloads.

Key Competencies

Data Engineering & Architecture
GCP Cloud Data Platforms
Healthcare Data Engineering
ETL/ELT Development
Data Modeling
Performance Optimization
Data Quality & Governance
Production Support & Troubleshooting
Problem Solving & Analytical Skills
Stakeholder Collaboration

Location and Work Style

Irving, TX (hybrid)

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2d ago

Principal Data Engineer

Optum Schaumburg, IL 🇺🇸 Remote

Schaumburg, IL

2d ago

$113k - $193k/yr Full time Azure Big Data Bigdata

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Job Description

As a Principal Data Engineer at Optum, you will support the RxMax application by helping build and strengthen scalable, secure, and resilient data platforms. This remote role in Schaumburg, IL focuses on delivering tailored solutions, troubleshooting enterprise data pipelines, and ensuring compliance with CMS-related requirements across Commercial Rebates and Medicaid Rebate systems. You will also leverage enterprise-approved AI tools to streamline workflows, automate routine tasks, and improve engineering productivity.

What you’ll do

Learn and apply complex healthcare business domain concepts, including rebates and CMS guidelines, to deliver data solutions aligned to business needs
Partner with software engineers, data architects, and business stakeholders to translate complex requirements into robust technical designs
Define and uphold high standards for data quality, data governance, security, and compliance across data integration workflows
Troubleshoot complex data pipelines, resolve system performance issues, and address data integration challenges using analytical problem-solving skills
Lead architecture, design, and implementation of scalable, high-performance data pipelines and enterprise data assets
Use enterprise-approved AI tools to streamline engineering workflows, automate routine data tasks, and drive continuous process improvement
Evaluate emerging technology trends and AI tools to inform data solution design and strategic technical innovation
Provide mentorship and application guidance to business and development teams for enhancements that support changing business environments
Communicate effectively in both oral and written form across cross-functional engineering, business leadership, and stakeholder groups
Maintain flexibility to work additional hours as needed to meet critical business needs and project deadlines

Required experience

5+ years working in production data environments while maintaining standards for data accuracy, governance, and security
5+ years advanced proficiency in SQL and at least one language such as Python, Scala, or Java
5+ years experience with cloud data platforms (e.g., AWS, Azure, or Snowflake) and big data frameworks (e.g., Spark or Databricks)
Experience working with or supporting financial systems and financial data architectures
Healthcare industry experience and familiarity with healthcare data models and standards, including HL7, FHIR, and HIPAA compliance
Demonstrated experience working with business teams from an operational standpoint
Demonstrated ability to use digital and productivity-enhancing tools to streamline engineering workflows and problem-solving

Technologies you’ll work with

SQL, Python, Scala, Java, AWS, Azure, Snowflake, Spark, Databricks, HL7, FHIR

Benefits and compensation

Comprehensive benefits package
Incentive and recognition programs
Equity stock purchase
401k contribution
Salary range: $112,700 - $193,200 per year

Preferred qualifications

Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field
Relevant cloud or data platform certifications (e.g., AWS Certified Data Analytics, Snowflake SnowPro Core, or Databricks Certified Data Engineer)
5+ years of experience working with cloud data platforms (e.g., AWS, Azure, Delta Lake, or Snowflake) and big data processing frameworks (e.g., Spark or Databricks)
Excellent oral and written communication skills with strong attention to detail and quality
Experience with healthcare rebate systems or Medicaid data platforms
Experience with IBMi DB2 systems and infrastructure
Experience designing, implementing, and maintaining a FISMA compliant environment supporting federal government applications and data
Solid knowledge of NIST 800-53 security controls, risk management frameworks (RMF), security authorization (ATO), and continuous monitoring practices
Experience implementing and managing security controls across cloud and on-premises environments, including identity and access management, encryption, vulnerability management, audit logging, and incident response
Demonstrated capability to rapidly learn and apply complex business domain concepts
Demonstrated ability to work independently and collaboratively in a fast-paced environment under strict time constraints and shifting priorities
Knowledge of Centers for Medicare & Medicaid Services (CMS) regulations, guidelines, or data standards
Experience with streaming data architectures and real-time processing platforms (e.g., Apache Kafka, Spark Streaming)

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2d ago

Senior Data Engineer – Microsoft Fabric & Healthcare Integrations

Quantum Pain & Sports Medicine Irving, TX

Irving, TX

2d ago

$125k - $150k/yr Full time Senior Analytics Automation Developer

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Job Description

Quantum Pain & Sports Medicine is building a centralized data and analytics platform in Microsoft Fabric, with a focus on dependable healthcare and business integrations. This Senior Data Engineering role is centered on infrastructure and ingestion pipelines in Fabric, so trusted, analytics-ready datasets can power reporting, operational analytics, automation, and future AI use cases.

You will help design the foundation early, implement the ingestion and data layers that make data reliable, and operate the platform so additional systems and new analytics needs can be added without rebuilding everything.

What you will do

Design and implement the Microsoft Fabric data architecture using OneLake, Lakehouse/Warehouse, Data Factory pipelines, notebooks, and related Fabric services.
Build and maintain ingestion pipelines from eClinicalWorks, HubSpot, APIs, databases, files, and future enterprise systems.
Integrate healthcare and operational systems using REST APIs, FHIR APIs, webhooks, batch exports, and other extraction approaches.
Implement a medallion-style structure with raw, validated, and analytics-ready layers.
Clean, standardize, deduplicate, and reconcile data across systems, including building patient, referral, appointment, provider, procedure, case, outcome, and other operational data models.
Create matching methods for records when identifiers are inconsistent or unavailable.
Deliver reusable curated datasets that support Power BI reporting, operational analytics, automation, and future AI applications.
Implement incremental loading, change detection, schema management, error handling, logging, alerting, and pipeline monitoring.
Set up data quality checks to identify incomplete, inconsistent, or unexpected source data.
Apply healthcare-appropriate security, access controls, and governance practices.
Use Git and CI/CD so pipelines and transformations remain version-controlled, documented, and maintainable.
Monitor Fabric usage, performance, capacity, and cost as the platform grows.
Document architecture, data definitions, pipelines, dependencies, and operating procedures.
Maintain and improve the platform after initial implementation, rather than treating it as a one-time migration.
Assess existing systems, data sources, reporting requirements, and the Microsoft environment, then design and configure the initial Fabric architecture.

Required qualifications

4+ years of professional experience in data engineering, data platform, or data integration.
Hands-on experience building production solutions with Microsoft Fabric or a closely related Azure data stack.
Strong SQL skills.
Strong Python and/or PySpark skills.
Experience designing ETL/ELT pipelines and data ingestion frameworks.
Experience with Microsoft Fabric Lakehouse, OneLake, Data Factory/Pipelines, notebooks, Delta tables, or equivalent technologies.
Experience integrating third-party systems via REST APIs.
Experience implementing incremental data loads rather than relying only on full refreshes.
Strong understanding of dimensional modeling, relational modeling, lakehouse architecture, and analytics-oriented data modeling.
Experience troubleshooting API authentication, pagination, rate limits, schema changes, malformed records, pipeline failures, and other real-world integration issues.
Experience with Git, source control, and CI/CD practices.
Experience implementing monitoring, logging, data-quality validation, and alerting for production pipelines.
Ability to work independently and make practical architectural decisions while the platform is still being built.
Healthcare experience is strongly preferred.

Healthcare and integration experience (preferred)

Experience with healthcare EHR/EMR data and healthcare operational or clinical data models.
Experience with eClinicalWorks.
Experience with FHIR/HL7 and healthcare integration patterns.
Familiarity with HIPAA-regulated data environments.
Experience with patient identity matching or Master Patient Index concepts.
Experience with HubSpot APIs and CRM data.
Experience with Microsoft Entra ID and Azure security, and/or Microsoft Purview or other governance tools.
Experience with Power BI semantic models.
Direct eClinicalWorks experience is a major plus, but strong healthcare API/FHIR integration experience is sufficient if you can quickly learn new source systems.

Tools and technologies

Microsoft Fabric, OneLake, Lakehouse, Warehouse, Data Factory, Pipelines, Notebooks, Delta tables
REST APIs, FHIR APIs, Webhooks
Python, PySpark, Git, CI/CD
Power BI, eClinicalWorks, HubSpot, FHIR, HL7
Microsoft Entra ID, Azure security, Microsoft Purview, Master Patient Index

Compensation and work details

Location: Irving, TX (onsite)
Employment type: Full-Time
Work arrangement: In-Office
Compensation: USD 125,000 - 150,000 per year (depending on experience)

Benefits

401(k) and 401(k) matching
Dental insurance
Health insurance
Life insurance
Paid time off
Vision insurance

Role focus (what this is not)

This position is not a Power BI developer role with occasional data engineering responsibilities.
Power BI knowledge is helpful, but the primary responsibility is building the data infrastructure underneath reporting, analytics, automation, and AI.
The role requires comfort working at the level of APIs, pipelines, Python, SQL, data models, cloud architecture, security, and production operations.

What success looks like

Within the first year, establish a maintainable Microsoft Fabric environment where data from major systems is automatically collected, validated, standardized, and exposed through trusted datasets.
Reduce manual work by replacing analyst-led extraction and cleaning with centralized datasets that include clearly defined metrics and lineage.
Design the platform so additional sources, analytics use cases, automation, and AI capabilities can be added over time without rebuilding the underlying infrastructure.

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3d ago

Lead Clinical Data Engineer

Yale University New Haven, CT 🇺🇸 Remote

New Haven, CT

3d ago

$90k - $166k/yr Full time Backend Developer Manager Analytics

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Job Description

The Lead Clinical Data Engineer role at Yale University focuses on advancing the Aligned Data Warehouse (ADW) for biomedical research. This position supports data pipeline and ETL development, expands data integration capabilities, and enables downstream analytics and research data sharing initiatives for Yale School of Medicine and Yale New Haven Health System.

Role Summary

As a senior technical specialist, you will lead the design and development of the ADW and extend its functionality. The work includes integrating new data sources, building and maintaining ETL and data pipelines, and supporting analytics and research data sharing efforts. You will also help manage troubleshooting for ETL failures and ensure healthcare data privacy and security across relevant systems.

Key Responsibilities

Design, build, test, maintain, and control data pipelines and ETL jobs to integrate data into the ADW and other research databases.
Contribute to DevOps and documentation by developing standards and procedures for database and data pipeline design, operational management, and ongoing maintenance.
Design, build, test, maintain, and control additional data management processes, including management and loading of flat files in formats such as csv, tsv, pipe-delimited, XML, and JSON.
Facilitate design sessions, code walkthroughs, and peer reviews; produce technical documentation, SOPs, and KBAs.
Performance tune database objects, stored procedures, ETL jobs, and related scripts to optimize end-user queries and pipeline ETL processing.
Monitor scheduled ETL jobs and related processes to ensure expected operation and pipeline uptime.
Lead and coordinate troubleshooting and remediation of ETL job failures in a timely manner.
Provide world-class customer service in interactions with customers, stakeholders, and other teams.
Maintain patient privacy and the integrity and security of healthcare data in all databases and systems, including compliance with applicable laws, regulations, and institutional policies related to the Institutional Review Board (IRB), patient privacy, and IT cybersecurity.
Independently research and stay current on new and emerging technologies that Scientific Computing & Data could use to improve capabilities, efficiencies, quality, or operating costs.
Lead projects and data stewardship strategies.
Work with the DBA team and vendors to optimize data pipelines.
Assist with the design, build, test, and performance tuning of reports and dashboards in SSRS, Microsoft Power BI, or similar business intelligence tools.
Perform related duties as assigned or requested.

Required Qualifications

Extensive experience developing, automating, and optimizing data integration workflows with a focus on Microsoft Fabric Data Pipelines supporting large-scale ingestion, transformation, and integration workloads.
Proven ability to design, develop, and optimize scalable data models, semantic layers, and storage architectures for enterprise reporting, self-service analytics, operational intelligence, and advanced analytics initiatives.
Experience developing and maintaining Fabric Notebooks using PySpark, Spark SQL, and related technologies for transformation, enrichment, validation, and automation.
Demonstrated experience designing and implementing Microsoft Fabric Lakehouses, Warehouses, and enterprise data organization strategies supporting governance, performance, security, and scalability requirements.
Ability to collaborate with business stakeholders, analysts, architects, and technical teams to translate complex business requirements into scalable data engineering solutions.
A bachelor's degree in a related area and a minimum of four years of experience in the field or a related area.

Technologies

Microsoft SQL Server, T-SQL, SSIS, SQL Agent
Microsoft Fabric, Microsoft Fabric Data Pipelines, Microsoft Fabric Lakehouses, Microsoft Fabric Warehouses
Metadata-driven dynamic SQL
Linux, Windows
OMOP Common Data Model, OHDSI's Observational Medical Outcomes Partnership (OMOP) Common Data Model
SSRS, Microsoft Power BI
PySpark, Spark SQL, Fabric Notebooks
Large Language Models, GPU-based software
csv, tsv, pipe-delimited, XML, JSON
Epic's data warehouse; Epic's Clarity & Caboodle databases
PCORnet, OnCore, IRES - IRB

Preferred Qualifications

In-depth knowledge of technology areas impacting the role, including healthcare technology experience.
Experience integrating electronic health record (EHR), clinical, research, financial, or operational healthcare data in cloud-based analytics platforms.
Certification and experience with Epic’s Clarity & Caboodle databases.
Experience with the OMOP Common Data Model, PCORnet, and other research data models, including familiarity with research administrative systems such as OnCore or IRES - IRB.

Preferred Education and Experience

Master's degree.
Experience in data engineering, analytics engineering, or data integration, including at least five (5) years designing, developing, and maintaining enterprise-scale healthcare data platforms, ETL processes, and cloud-based data solutions.

Compensation, Work Model, and Employment Details

Location: New Haven, CT (remote)
Salary: USD 90,000 - 165,750 per year
Time type: Full time
Duration type: Staff
Work model: Remote
Job category: Professional
Compensation grade: Administration & Operations (Manager; Program Leader (P6))
Salary range: $90,000.00 - $165,750.00
Background check requirements: Pre-employment background screening may include motor vehicle, DOT certification, drug testing, and credit checks based on position description and job requirements; offers are contingent on successful completion.
Health requirements: Certain positions may require vaccinations, tests, or examinations as required by law, regulation, or university policy.

Benefits

A general description of benefits for this Managerial & Professional position is available at: Yale Benefits.

Additional Information

Job posting date: 10/13/2026
Bargaining unit: NON
Compensation grade profile: Manager; Program Leader (P6)
Posting disclaimer: Salary offers are determined by qualifications, experience, skills, and education relative to role requirements, along with the role’s grade profile and internal/external market conditions. The description provides a representative summary of essential functions and does not declare specific duties and responsibilities. Employees are assigned specific duties by the hiring department.
Note: Yale University is a tobacco-free campus.

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5d ago

Senior Data Engineer

Dell Medical School Austin, TX

Austin, TX

5d ago

$138k+/yr Full time Senior Apache Airflow Big Data

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Job Description

The Senior Data Engineer at Dell Medical School will lead the design, development, and optimization of complex data pipelines and platforms that enable enterprise analytics, reporting, and advanced data use cases across clinical, operational, financial, and research environments.

Key Responsibilities

Design, build, and maintain complex, scalable ETL/ELT pipelines for both structured and unstructured data.
Lead data integration from EHRs, financial systems, registries, and external data sources.
Optimize pipelines for performance, reliability, fault tolerance, and cost efficiency.
Implement batch and near-real-time processing patterns as needed.
Ensure pipelines meet regulatory, privacy, and security requirements, including HIPAA.
Serve as technical owner for assigned data platforms, domains, or subject areas (such as clinical analytics or operational reporting).
Design and maintain data lake, warehouse, and data mart structures using cloud platforms.
Develop and enforce data modeling standards, schema design practices, and partitioning strategies.
Partner with IT and cloud teams to support availability, scalability, and disaster recovery readiness.
Build curated, analytics-ready datasets and reusable data assets for analysts and data scientists.
Collaborate with data science teams to support feature engineering, model training, and deployment workflows.
Develop frameworks and patterns that improve self-service analytics and reduce ad hoc data requests.
Support predictive analytics and AI/ML proof-of-concept and experimentation efforts.
Improve data engineering workflows through automation, monitoring, and CI/CD for data pipelines.
Refactor legacy pipelines and supporting infrastructure to improve maintainability and scalability.
Establish best practices for code quality, documentation, testing, and version control.
Evaluate new tools and technologies and recommend adoption where appropriate.
Mentor Data Engineer staff and review code, pipeline designs, and architecture artifacts for quality and consistency.
Provide guidance on complex technical problems and help unblock team members.
Contribute to onboarding, internal training, and knowledge-sharing activities.
Partner with business, clinical, research, and operational stakeholders to translate requirements into technical solutions.
Lead data engineering workstreams within cross-functional projects or agile squads.
Communicate technical concepts, trade-offs, and risks to non-technical audiences.
Support planning, estimation, and prioritization of data engineering initiatives.
Support data integration efforts for new service lines, acquisitions, or system migrations.
Participate in vendor evaluations and technical assessments.
Assist with disaster recovery testing and business continuity planning.
Contribute to grant proposals or research initiatives requiring advanced data infrastructure.
Perform related duties as required.

Technologies

SQL, Python, Spark
Airflow
AWS, GCP, Azure/Fabric
HIPAA, HL7, FHIR

Requirements

Bachelor’s Degree in Computer Science, Data Engineering, Information Systems, or a related field.
At least 6 years of experience in data engineering, analytics engineering, or data platform development.
Demonstrated experience designing and leading complex data pipelines and data platforms.
Relevant education and experience may be substituted as appropriate.

Preferred Qualifications

Master’s Degree in Data Science, Data Engineering, Computer Science, Informatics, or related field.
Experience in healthcare data engineering or regulated data environments.
Exposure to AI/ML infrastructure, feature stores, or model operationalization.
Experience leading technical initiatives or acting as a team lead.

Preferred Certifications

Cloud Certification
Microsoft Certified: Azure Data Engineer Associate
Google Cloud Professional Data Engineer
AWS Certified Data Analytics – Specialty

Salary and Location

Location: Austin, TX (onsite)
Salary: USD 138,000 per year
Salary Range: $138,000+ depending on qualifications

Working Conditions

Standard office equipment
Repetitive use of a keyboard
May be exposed to healthcare-related occupational hazards depending on assignment

Required Materials

Resume/CV
3 work references with contact information (at least one reference should be from a supervisor)
Letter of interest

Certifications

Required: None

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6d ago

Senior Data Engineer (Healthcare)

VeeRteq Solutions Inc. Philadelphia, PA

Philadelphia, PA

6d ago

Full time Senior Analytics Automation Developer

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Job Description

Build and support cloud-based healthcare data platforms using Azure and Databricks.

Location: Philadelphia, PA (hybrid)
Experience: 7+ years

Responsibilities

Build and maintain ETL/ELT data pipelines.
Develop data solutions using Azure Databricks, Azure Data Factory (ADF), and Azure Data Lake Storage (ADLS Gen2).
Create and optimize PySpark and SQL data processing frameworks.
Implement Delta Lake and Lakehouse architectures.
Support data migration, modernization, and cloud transformation initiatives.
Ensure data quality, reliability, and performance across pipelines and downstream reporting.
Build data models and curated datasets used for reporting and analytics.
Implement CI/CD, monitoring, and DevOps best practices for data services.
Collaborate with business users, architects, and product teams in an Agile environment.

Requirements

Azure Databricks
Azure Data Factory (ADF)
Azure Data Lake Storage (ADLS Gen2)
PySpark and Python
SQL
Delta Lake
Data Modeling
ETL/ELT development
Azure Cloud Platform
Git & CI/CD
Agile/Scrum

Preferred Skills

Azure Synapse Analytics
Power BI
Azure DevOps
Infrastructure as Code (IaC)
FHIR/HL7
AI/ML Data Pipelines

Required Experience

7+ years in Data Engineering
5+ years with Azure Data Technologies
2+ years in Healthcare, including Payer, Health Plan, or Managed Care domains
Experience with large-scale data pipelines and integration solutions

Nice to Have

Claims Data
Membership Data
Provider Data
Care Management Data

Technologies

Azure Databricks
Azure Data Factory (ADF)
Azure Data Lake Storage (ADLS Gen2)
PySpark, Python, SQL
Delta Lake
Azure Cloud Platform
Git, CI/CD
Lakehouse architectures
DevOps
Azure Synapse Analytics
Power BI
Azure DevOps
Infrastructure as Code (IaC)
FHIR/HL7
AI/ML Data Pipelines

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Healthcare Data Engineering Jobs

Analytics Engineer

Senior Data Engineer

Principal Data Engineer

Senior Data Engineer – Microsoft Fabric & Healthcare Integrations

Lead Clinical Data Engineer

Senior Data Engineer

Senior Data Engineer (Healthcare)

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