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Azure Analytics Data Jobs

6 jobs found

Today

Sr. Azure Data Engineer with Databricks

VeeRteq Solutions Inc. Philadelphia, PA

Philadelphia, PA

Today

Full time Azure Azure Analytics Azure Data Engineer

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Job Description

Build and optimize enterprise Azure and Databricks data platforms in a hybrid role based in Philadelphia.

Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines for enterprise data and analytics initiatives
Build data ingestion, transformation, and orchestration frameworks using Azure-native technologies
Develop and optimize data processing solutions using Databricks and PySpark
Implement and maintain Delta Lake and Lakehouse architectures
Ensure data quality, accuracy, lineage, and reliability across data assets
Perform root cause analysis and troubleshoot data-related issues
Work on solutions leveraging:
- Azure Databricks
- Azure Data Lake Storage (ADLS Gen2)
- Azure Data Factory (ADF)
- Azure Synapse Analytics
- Azure SQL Database
Support data migration, modernization, and cloud transformation efforts
Optimize performance, scalability, and cost efficiency for cloud-based data platforms
Build and maintain logical and physical data models
Create curated data layers for BI, reporting, and advanced analytics
Partner with business users and data consumers to translate requirements into scalable technical solutions
Implement CI/CD processes for data engineering solutions and support automated deployment and release management
Develop monitoring, logging, and observability capabilities for data pipelines
Follow enterprise data governance and security standards
Participate in Agile/Scrum ceremonies including sprint planning, daily stand-ups, retrospectives, and backlog refinement
Collaborate with Product Owners, Architects, QA teams, and business stakeholders
Contribute to continuous improvement and engineering best practices

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field
7+ years of experience in Data Engineering
5+ years hands-on experience with Azure data technologies
2+ years experience in Healthcare, Managed Care, Health Plans, or Payer organizations
Strong expertise in:
- Azure Databricks
- Azure Data Lake Storage (ADLS)
- Azure Data Factory (ADF)
- PySpark
- Python
- SQL
- Delta Lake and Data Modeling
Extensive experience building enterprise-scale data pipelines and data integration solutions
Strong understanding of Data Warehousing, Data Lake, and Lakehouse concepts
Experience with large volumes of structured and unstructured data
Experience with Git, CI/CD, and DevOps practices
Strong analytical, troubleshooting, and problem-solving skills

Required Technical Skills

Must Have: Azure Databricks
Must Have: Azure Data Lake (ADLS Gen2)
Must Have: Azure Data Factory (ADF)
Must Have: PySpark
Must Have: Python
Must Have: SQL
Must Have: Delta Lake
Must Have: Data Modeling
Must Have: ETL/ELT Development
Must Have: Azure Cloud Platform
Must Have: Git
Must Have: CI/CD
Must Have: Agile/Scrum
Skills: Azure Synapse Analytics, Azure SQL Database

Preferred Qualifications

Experience working with: Claims Data, Membership Data, Provider Data, Care Management Data
Experience with Power BI or other reporting tools
Familiarity with FHIR, HL7, or healthcare interoperability standards
Experience with Azure DevOps and Infrastructure as Code (IaC)
Exposure to AI/ML data pipelines and advanced analytics environments

Location & Work Model

Philadelphia, PA (hybrid)
Onsite presence required at least three days per week

Technology Stack

Azure, Databricks, Azure Databricks, PySpark, Python, SQL
Delta Lake and Lakehouse architectures, ETL/ELT
Azure Data Lake Storage (ADLS Gen2), Azure Data Lake Storage (ADLS)
Azure Data Factory (ADF), Azure Synapse Analytics, Azure SQL Database
Git, CI/CD, Agile/Scrum, Data Modeling

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13d ago

Data Scientist

Analytica Bethesda, MD

Bethesda, MD

13d ago

Full time Python Analytics Artificial Intelligence

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Job Description

Analytica is hiring a Data Scientist in Bethesda, MD (onsite) to lead statistical and AI/ML work for product safety analytics.

Responsibilities

Use semantic coding and analysis to identify patterns and thematic insights across structured and unstructured data
Convert analytical results into actionable insights using data storytelling and visualization techniques
Develop interpretable and explainable analytics outputs to support decision-making
Design, implement, and maintain AI/ML models, including product similarity models
Build models using supervised and unsupervised learning approaches
Create and maintain models for anomaly detection, classification, regression, and pattern recognition
Assess model quality with robust performance metrics such as precision, recall, F1-score, and AUC to support accuracy, reliability, and fairness
Continuously improve performance through testing, validation, and tuning
Evaluate emerging technologies and new methodologies to address complex analytical problems
Apply modern development tools and frameworks (including GitHub Copilot and CI/CD pipelines) to streamline workflows and improve delivery efficiency
Optimize data science workflows for scalability and performance in cloud environments (Azure)

Requirements

Bachelor’s Degree required; Master’s degree or Ph.D. preferred in Data Science, Machine Learning, Computer Science, Mathematics, or a related field
5+ years of experience developing statistical and AI/ML models with modern tools and best practices
3+ years building predictive models, including regression, classification, and NLP applications
3+ years hands-on experience with Python (including Pandas, Scikit-learn, PyTorch, or TensorFlow)
3+ years experience working in cloud environments (Azure preferred)
2+ years experience with SQL for data querying and manipulation
Strong experience with data visualization tools such as Power BI (or equivalent)
Proven ability to apply semantic analysis or coding techniques within ML workflows
Strong written and verbal communication skills, including the ability to explain technical concepts clearly
Experience using Git-based version control for collaborative development
Ability to work in Agile teams, contributing to sprint planning and iterative development
Proven experience collaborating with technical and business stakeholders to deliver high-quality, data-driven solutions

Technologies

AI/ML
Python (Pandas, Scikit-learn, PyTorch, TensorFlow)
SQL
Power BI
GitHub Copilot
CI/CD pipelines
Azure
NLP

Benefits

Bonuses
Employer paid health care
Training and development funds
401k match
Competitive compensation

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14d ago

Senior Data Analytics Engineer

Microsoft United States

United States

14d ago

$106k - $223k/yr Full time Senior Analytics Artificial Intelligence

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Job Description

This role is a platform-focused Senior Data Analytics Engineer position at Microsoft, based in the United States (onsite). The work centers on designing and operating real-time and batch data pipelines, governed semantic models, and serving infrastructure that supports CSS intelligence and detection products.

Role Summary

Own the end-to-end systems that power detection intelligence, including pipeline reliability, data quality and observability, and productionization of AI decision systems. The role emphasizes governed certified measures and traceable query paths rather than reporting dashboards.

Key Responsibilities

Design and operate data pipelines feeding CSS intelligence, covering batch processing at organizational volume and near real-time streams where detection latency matters.
Ingest case and agent telemetry, integrate with the unified data platform and Finance systems, and build scoring pipelines that run data science models continuously in production.
Ensure pipeline reliability through monitoring and alerting, addressing schema drift and late-arriving data, and escalating failures promptly so issues surface before executive review.
Build and own the semantic layer between raw data and consuming experiences, including dimensional models, certified measures with documented definitions and clear ownership, consistent hierarchies, and security context for data access.
Support detection engine queries and executive natural-language experiences via a semantic API, enabling governed measures with a traceable query path instead of improvised calculations.
Embed data quality and observability into pipelines using freshness stamps, reconciliation tests against sources of record, data contract checks, and end-to-end lineage for tracing numbers back to their underlying rows.
Apply engineering practices to analytics using source control, deployment pipelines, environment separation, and infrastructure defined as code; manage cost and performance through partitioning, incremental refresh, and query optimization.
Partner with data scientists and applied AI engineers to convert experimental models into production services and prepare data for AI consumption, including grounding, retrieval, and feature-serving patterns used by agents.
Design for team handoff with legible schemas, APIs, deployment approaches, and documentation for downstream teams.

Required Qualifications

Education and experience: Master’s Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics, or a related field and 2+ years of experience in data analysis and reporting, data science, business intelligence, or business and financial analysis; or Bachelor’s Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics, or a related field and 4+ years of experience in data analysis and reporting, data science, business intelligence, or business.
Hands-on experience with Microsoft Fabric, Azure Synapse, Azure Data Factory, Databricks, or Power BI semantic models in a production environment.
Experience building data platforms for AI or machine learning workloads, including feature serving, retrieval and grounding data, or model scoring at scale.
Experience implementing data governance in practice, including certified metric definitions, tiered metric ownership, and promotion processes for executive reporting.
Experience supporting executive-facing analytics where accuracy, freshness, and traceability are required.

Technologies

SQL, Python, Spark, PySpark, Microsoft Fabric, Azure Data Factory, Azure Synapse, Databricks, DAX, Power BI
CI/CD, Infrastructure as code, API, Natural language, Azure

Core Skills and Experience

Deep SQL expertise and strong Python skills, including distributed processing with Spark or PySpark.
Experience building production pipelines in batch and streaming or near real-time modes on platforms such as Microsoft Fabric, Azure Data Factory, Synapse, Databricks, or equivalents.
Strong dimensional and semantic modeling, including star schema design, tabular or semantic models, and calculation languages such as DAX, with discipline around certified single-definition measures.
Experience with layered architectures that separate raw, conformed, and serving tiers, including knowing which transformations belong in each tier.
Ability to expose data and measures programmatically through APIs or query services for applications, services, or AI agents, not only reporting tools.
Data quality and observability practices, including reconciliation testing, data contracts, freshness and completeness monitoring, anomaly detection, and end-to-end lineage.
Software engineering discipline for data work, including source control, CI/CD, deployment pipelines, environment separation, code review, and infrastructure as code.
Platform cost and performance optimization through partitioning, incremental refresh, aggregation strategy, capacity management, and query tuning.
Experience preparing data for AI and machine learning consumption, including feature pipelines, grounding and retrieval patterns, embedding or vector stores, and modeling agent telemetry (identifiers, token usage, evaluation output).
Collaboration with data scientists to productionize models and with business stakeholders to translate operational questions into durable data designs.
A platform mindset focused on reusable, documented capability and recognition of when governed measures already answer a question.
Comfort operating with autonomy on a small team, owning components end to end, and writing documentation so others can run the work.

Examples of Work in This Role

Build a certified measure layer used consistently by the detection engine, executive brief experiences, natural-language interactions, and monthly review content to prevent surface-level recalculation.
Design a semantic API and query service that lets an AI agent answer questions against governed measures under the requester’s security context, including freshness and query traceability.
Stand up continuous scoring pipelines that compute case propensity and complexity models across CSS case volume and deliver results to detection and workflow systems.
Ingest AI agent telemetry including agent identifiers, model and version, token consumption, and evaluation results, then model the data to compare quality and cost across platforms.
Deliver detection infrastructure that computes baselines, thresholds, and materiality gates on a schedule and routes validated signals into notification and workflow paths.
Implement reconciliation and freshness monitoring to automatically catch and attribute discrepancies between the platform and sources of record.
Establish deployment, versioning, and documentation patterns to hand capabilities to partner engineering teams for broader operation.

Preferred or Additional Qualifications

Master’s Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics, or a related field and 6+ years of experience in data analysis and reporting, data science, business intelligence, or business and financial analysis; or Bachelor’s Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics, or a related field and 8+ years of experience in data analysis and reporting, data science, business intelligence, or business.

Location and Compensation

Location: United States (onsite)
Salary Range: USD 106,400 - 222,600 per year
Minimum Experience: 2 years

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1mo ago

Lead Data Scientist

Copper Hill Charlotte, NC

Charlotte, NC

1mo ago Closed

Full time Backend Developer Manager Analytics

This position is no longer accepting applications (closed Sep 18, 2026).

Job Description

Lead advanced analytics and machine learning initiatives for a SaaS platform in a hybrid role based in Charlotte, NC.

Responsibilities

Lead development of data validation methodologies
Build and lead delivery of predictive models and machine learning solutions
Create training materials explaining Generative AI vs AI writ large
Define data science methodologies and best practices
Mentor data scientists and analysts
Translate business requirements into analytical solutions
Develop machine learning models for classification, regression, clustering, and forecasting
Optimize model performance and accuracy
Establish testing methodologies to measure performance on queries across frontier model providers (e.g., OpenAI, Anthropic, Perplexity, Cohere)
Implement reinforcement learning structures supporting different AI model providers
Develop experimentation frameworks and A/B testing approaches
Collaborate with engineering teams to design scalable data pipelines
Support production deployment of models
Ensure data quality and reproducibility
Partner with Product Management on data-driven product features
Embed machine learning capabilities into the SaaS platform
Design APIs and services that expose model outputs to the application
Develop solutions using Microsoft Azure data services
Work with SQL Server and large structured datasets
Support model deployment and monitoring in cloud environments

Requirements

7+ years of experience in data science or machine learning
Experience deploying machine learning models into production systems
Strong experience with Python or R, SQL, and machine learning frameworks

Technologies

Microsoft Azure
SQL Server
C#
Angular
Python
R
OpenAI
Anthropic
Perplexity
Cohere

Benefits

401(k)
401(k) matching
Dental insurance
Flexible schedule
Health insurance
Life insurance
Paid time off
Retirement plan
Vision insurance

Work Location

Hybrid remote in Charlotte, NC

Reports To

Vice President of Engineering

Employment Type

Full-Time

Preferred Experience

Experience with Azure Machine Learning or cloud ML platforms
Experience working with enterprise datasets or SaaS platforms
Advanced degree in Data Science, Computer Science, Statistics, or related field

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1mo ago

Data Analytics Engineer

Collins Aerospace Santa Isabel, Puerto Rico 📍 Santa Isabel Remote

Santa Isabel, Puerto Rico

1mo ago Closed

Full time Azure Analytics Azure Data Lake Big Data

This position is no longer accepting applications (closed Sep 14, 2026).

Job Description

This Data Analytics Engineer role focuses on building dependable data pipelines, models, datasets, and analytics solutions that support business performance and AI/ML initiatives.

Responsibilities

Design, build, and maintain reliable, scalable data pipelines, data models, and curated datasets for analytics, reporting, decision-making, and AI/ML use.
Integrate, transform, standardize, and validate data from diverse, non-standard sources including enterprise applications, spreadsheets, databases, text files, APIs, and operational data sources.
Develop and maintain data visualization, statistical analysis, reporting, and analytical solutions to improve understanding of enterprise and infrastructure data.
Establish and improve data quality, validation, monitoring, governance, documentation, and data management practices for trusted and reusable data.
Partner with customers and stakeholders to understand business and operational needs, spot opportunities for improvement, and translate requirements into practical data and analytical solutions.
Independently lead projects using appropriate software development and agile practices, covering requirements and solution design through development, testing, implementation, and continuous improvement.
Create and maintain technical and business documentation, including requirements, data definitions, process flows, use cases, user stories, technical designs, and operational procedures.
Provide data engineering and analytical support for AI/ML initiatives, including data preparation, feature development, dataset creation, experimentation support, evaluation, and integration of AI/ML outputs into operational solutions.
Collaborate cross-functionally across IT and operations, providing technical guidance, peer review, and mentoring within the Data & Insights team.
Apply information security, information assurance, governance, privacy, and compliance requirements across data, analytics, and AI/ML activities.
Use written work instructions as guidance for daily job activities.

Requirements

Education: University Degree (or equivalent experience); Advanced Degree in a related field (alternative).
Experience: Minimum 8 years prior relevant experience (or 5 years with an Advanced Degree in a related field).
5+ years of experience in data engineering, data analytics, business intelligence, or a related technical discipline.
Hands-on experience with Python and SQL, including PySpark or comparable distributed data-processing technologies.
Proven experience designing and developing production-quality data pipelines, data models, ETL/ELT, and data integration solutions.
Experience with data quality, data governance, data warehousing, data modeling, and modern cloud data architectures.
Ability to analyze complex datasets, develop meaningful metrics and visualizations, and translate results into actionable insights and recommendations.
Experience independently owning technical projects and delivering solutions with limited day-to-day direction, including working through ambiguous or complex problems.
Experience structuring and curating data to support machine learning, AI/ML, advanced analytics, or other data science applications.

Technologies

Python
SQL
PySpark
ETL/ELT
Azure
Databricks
Snowflake
Delta Lake
Power BI
ServiceNow/ITSM data
Git/CI/CD

Benefits

Healthcare
Wellness
Retirement
Work/life benefits
Parental (including paternal) leave
Flexible work schedules
Achievement awards
Educational assistance
Child/adult backup care

U.S. Citizenship Requirements

U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.

Security Clearance

None/Not Required

Location and Remote Details

Remote role (primarily offsite from home).
Successful candidate must be currently living in Puerto Rico.
May be expected to travel to the Santa Isabel site location as needed.

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2mo ago

BI & Analytics Analyst/Data Engineer

Jewish Council for the Aging of Greater Washington Rockville, MD

Rockville, MD

2mo ago Closed

$110k - $132k/yr Full time Analyst Analytics Azure Analytics

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

The BI & Analytics Analyst/Data Engineer is responsible for engineering, development, support, and management of data and analytics solutions across the agency. This hybrid role splits time evenly between business intelligence delivery and hands-on data engineering, with ownership of the end-to-end analytics lifecycle and development of self-service Power BI reporting.

Responsibilities

Partner with IT business stakeholders and operational leaders to design analyses that identify opportunities for improvement in care, assess adherence to clinical best practices, and measure outcomes.
Help ensure agency data repositories provide consistent, reusable data by collaborating with key staff to develop, implement, and advise on data standards and best practices.
Promote best-practice knowledge and enable business stakeholders to conduct self-service analysis rather than relying on IT-owned development.
Own self-service reporting datasets, including DAX measures, data models, and row-level security.
Translate business needs into clear analytical deliverables, manage stakeholder expectations, and iterate based on feedback.
Monitor report usage and data quality, proactively identifying and resolving issues.
Document data definitions, metric logic, and report lineage to support a data-literate culture across the agency.
Use technical tools to query, manipulate, and summarize data from multiple data sources.
Assist in designing, developing, maintaining, and updating databases to meet department and organizational needs.
Design and build star schema data warehouse objects in SQL Server, including fact tables, dimension tables, and aggregate layers.
Write and maintain T-SQL stored procedures, ETL pipelines, and staging-to-DWH data loads.
Develop and maintain source-to-target mapping documentation for new data domains.
Integrate data from source systems.
Contribute to data quality, pipeline reliability, and warehouse performance optimization.
Support self-service analytics adoption by building clean, well-documented datasets.
Document current data architecture, define logical and physical data, and establish an agency data blueprint.
Manage and support the data warehouse solution (Wherescape RED), SQL Server, and associated components.
Define operational monitoring and alerting tools to ensure trusted, high-quality data flows from source systems to consumption.
Establish best-practice standards and processes for data automation, orchestration, and transformation.
Identify, design, implement, and manage a master data management solution for client and employee subjects, including defining data quality standards and operational data quality processes with stakeholders.

Requirements

Bachelor’s degree required; Master’s degree highly preferred.
5-7+ years of experience in a BI, analytics, or data engineering role.
Strong proficiency in SQL Server and T-SQL, including stored procedures, window functions, and query optimization.
Hands-on experience building and maintaining Power BI reports and semantic models (DAX, Power Query).
Hands-on experience with Wherescape OLAP; experience with alternative OLAP solutions including Azure Analysis Service, Azure Data Lake, and Azure Synapse Analytics.
Experience integrating or working with EHR data (reports, APIs, or data exports).
Familiarity with star schema and dimensional modeling concepts (Kimball methodology a plus).
Python experience for data wrangling, automation, or pipeline scripting.
Experience with Microsoft Master Data Services (MDS), including defining entities and creating business rules.
Experience with Microsoft Data Quality Services (DQS) and SQL Server Integration Services (SSIS).
Comfortable working across the full analytics stack, from raw source data to end-user reporting.
Strong communication skills, including explaining data concepts clearly to non-technical stakeholders.
Advanced skill set with the Microsoft Office suite (Power BI), SQL, and experience with EMR systems (hospice, homecare, and/or mental health) desired.

Technologies

SQL Server, T-SQL, ETL
Power BI, DAX, Power Query
Wherescape OLAP, Wherescape RED
Azure Analysis Service, Azure Data Lake, Azure Synapse Analytics
Python
Microsoft Master Data Services (MDS)
Microsoft Data Quality Services (DQS)
SQL Server Integration Services (SSIS)
EHR data, EMR systems
Master data management

Job Details

Location: Rockville, MD (Hybrid)
Experience: 5+ years
Salary: USD 110,000 - 132,000 per year

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