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Data Engineer

Booz Allen Hamilton Camp Lejeune, NC

Camp Lejeune, NC

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$78k - $176k/yr Full time Data Data Analysis Data Analytics

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Job Description

Booz Allen Hamilton is seeking an experienced Data Engineer to deliver mission-driven data engineering and analytic solutions on an onsite basis.

Responsibilities

Implement data engineering activities on mission-driven projects
Deploy and develop pipelines and workflows that organize disparate data and make it meaningful
Partner with and guide a multi-disciplinary team including analysts, data engineers, developers, and data consumers in a fast-paced, agile environment
Conduct analytical exploration and data examination while managing assessment, design, building, and maintenance of analytic solutions for clients

Requirements

Experience using programming and querying languages: Python, R, Scala, and/or SQL
Experience developing and maintaining data applications for reporting and analytics
Experience building software to retrieve, parse, and process structured and unstructured data
Experience creating scalable ETL or ELT workflows for reporting and analytics
Experience delivering solutions in a collaborative, cross-functional team environment
Ability to obtain a Secret clearance
HS diploma or GED

Technology

Python
R
Scala
SQL
ETL
ELT

Benefits

Health benefits
Life insurance
Disability benefits
Financial benefits
Retirement benefits
Paid leave
Professional development
Tuition assistance
Work-life programs
Dependent care
Recognition awards program

Clearance Information

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information

Identity Verification

As part of the hiring process, you will complete an identity verification process using advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud
You are expected to be on camera during interviews and assessments
Booz Allen reserves the right to take your picture to verify your identity and prevent fraud

Candidate AI Usage Policy

AI is part of daily work, with a commitment to responsible and ethical use
Using artificial intelligence (AI) or other tools to assist with responses during interviews (in-person or virtual) is prohibited unless permission is explicitly provided

Compensation

Projected compensation range: $77,500 to $176,000 per year (annualized USD)
Salary is determined by factors including location, education, knowledge, skills, competencies, experience, and contract-specific affordability and organizational requirements
This posting will close within 90 days from the Posting Date

Work Model

Onsite: Work will primarily be performed full-time at a customer facility, with collaboration with colleagues and customers as required
Employees working virtually are generally expected to have their cameras on during meetings

Non-Discrimination Commitment

All qualified applicants receive consideration for employment without regard to disability, protected veteran status, or any other status protected by applicable federal, state, local, or international law.

Location: Camp Lejeune, NC (onsite)

Education: HS diploma or GED

Salary: USD 77,500 - 176,000 per yearly

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Senior Data Engineer - Sr Consultant - AI&E

Deloitte Philadelphia, PA

Philadelphia, PA

Today

Full time Senior Apache Airflow Artificial Intelligence

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Job Description

Deloitte seeks a Senior Data Engineer (Sr Consultant) to design, develop, and operationalize scalable healthcare data platforms and integration pipelines spanning multiple healthcare domains. The position supports delivery of cloud-based data products using specified technologies and follows Deloitte’s Project Delivery Talent Model.

Key Responsibilities

Design, develop, and operationalize scalable healthcare data platforms
Design and develop integration pipelines across healthcare domains including claims, payments, member, provider, eligibility, medical, and pharmacy

Required Qualifications

6+ years of experience designing healthcare data platforms
Deep knowledge of Cigna Medicare business
Bachelor’s degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline, or equivalent experience
Limited immigration sponsorship may be available
Ability to travel 10%, on average, based on work performed and client and sector needs

Technologies

Azure Databricks
PySpark
Python
AWS services
Teradata Vantage
Informatica
Airflow
GitHub
Azure DevOps

Additional Preferred Focus

Analytical and decision-making responsibilities
Analytical ability to manage multiple projects and prioritize tasks into manageable work products
Ability to operate independently or with minimum supervision
Excellent written and communication skills

Location and Work Model

Philadelphia, PA (onsite).

Applicant Accommodation Information

For applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

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Databricks Engineer - Data Engineer II

Deloitte Washington, DC

Washington, DC

Today

$98k - $163k/yr Full time Backend Developer Big Data Bigdata

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Job Description

Join Deloitte’s AI & Engineering team as a Databricks Engineer II, focused on building and improving data pipelines on the Databricks Lakehouse platform. In this onsite role in Washington, DC, you will apply Medallion architecture patterns, strengthen data governance with Unity Catalog security controls, and support reliable Databricks workflows through testing and CI/CD.

Location: Washington, DC (onsite)
Compensation: USD 97,700 - 162,800 per year
Experience: 2+ years
Education: Bachelor’s degree

What you will do

Develop and optimize data pipelines using Python, PySpark, and SQL on the Databricks Lakehouse platform
Use Medallion architecture to organize, transform, and manage data across data layers
Perform performance tuning for Databricks workloads and SQL queries
Configure row-level and column-level security, and manage data lineage and data sharing in Unity Catalog
Implement CI/CD and testing processes for Databricks workflows

What you bring

Bachelor’s degree
Ability to obtain and maintain the required clearance for this role
2+ years of Databricks engineering experience
2+ years of experience with Python, PySpark, and SQL
Ability to travel 10-15% on average based on work, clients, and industries/sectors served
Must be legally authorized to work in the United States without employer sponsorship, now or in the future

Technologies

Python
PySpark
SQL
Databricks Lakehouse platform
Unity Catalog

Skills a successful candidate will demonstrate

Ability to work independently and collaborate within a team
Effective written and verbal communication skills
Meticulous attention to detail and focus on work quality
Ability to build and sustain professional relationships
Ability to lead projects or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to provide clear guidance to others

Preferred qualifications

Experience using Medallion architecture on the Databricks Lakehouse platform
Experience configuring row-level and column-level security, data lineage, and data sharing in Unity Catalog
Experience implementing CI/CD and testing processes for Databricks
Experience with performance tuning in Databricks

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Senior Data Engineer

Mayo Clinic Rochester, MN

Rochester, MN

Today

$137k - $206k/yr Full time Senior Business Intelligence Data Analytics

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Job Description

Mayo Clinic is seeking a Senior Data Engineer to help build and run data pipelines, integrations, and transformations that power analytics and machine learning. In this hybrid role in Rochester, MN, you will contribute to medication management reporting and analytics while designing and maintaining medication-related data architectures across Microsoft Fabric and Google BigQuery.

Working as part of an assigned product team, you will develop SQL-based reporting solutions delivered via Power BI and/or Tableau dashboards, and partner with product owners and analytics and machine learning delivery teams to retrieve data, explore it, and identify trends through robust pipelines.

Responsibilities

Develop and deploy data pipelines, integrations, and transformations to support analytics and machine learning applications using open-source programming languages and vended software.
Maintain current knowledge of the organization’s solutions, coding languages, and tools, using independent judgment to support delivery.
Provide consultative services to departments, divisions, and leadership committees.
Design, build, and implement data systems and their application within the Department of Data & Analytics technology framework.
Partner with product owners and Analytics and Machine Learning delivery teams to identify, retrieve, and explore data; then pipeline and transform it to surface and visualize trends.
Build and validate analytical models and translate qualitative and quantitative assessments into actionable insights.
Create complex SQL-based reporting solutions delivered through Power BI and/or Tableau dashboards.
Design and maintain medication-related data architectures in Microsoft Fabric and Google BigQuery (via Google Cloud Data Fusion).
Support the Pharmacy Informatics Reporting Team, including medication-related reporting in Epic (such as SlicerDicer, dashboards, metrics, reporting workbench reports, Caboodle, and Clarity), and analytics/reporting for ancillary systems including BD Pyxis, BD logistics, BD CII safe systems, pharmacy purchasing data, operating room medication systems, retail pharmacy systems, inpatient automation technologies, and other medication management technologies.

Requirements

Advanced SQL experience.
Prior experience working with healthcare data.
Experience developing and deploying data pipelines from multiple sources, including databases, APIs, and file systems.
Experience leveraging cloud-based tools in Google Cloud or Microsoft Fabric.
Programming experience (for example: Python, JavaScript, PHP, C++, or Java and API integration).
Excellent communication skills.
Commitment to ongoing skill development and continuous learning.
Bachelor’s degree in a relevant field (or Associate’s degree with additional experience) paired with minimum experience requirements related to data visualization, data engineering, and analytical modeling techniques.
In-depth business or practice knowledge will also be considered.

Technologies

SQL, Power BI, Tableau, Microsoft Fabric, Google BigQuery, Google Cloud Data Fusion
Python, JavaScript, PHP, C++, Java
Epic, SlicerDicer, Caboodle, Clarity
BD Pyxis, BD logistics, BD CII safe systems

Preferred

Google BigQuery and Google Cloud Data Fusion experience
Google Cloud Professional Data Engineer Certification
Tableau experience
Power BI experience
Epic Clarity/Caboodle certification

Compensation & Benefits

Salary: USD 137,134 - 205,691 per year (education, experience, and tenure may be considered with internal equity).
Medical: Multiple plan options
Dental: Delta Dental or reimbursement account for flexible coverage
Vision: Affordable plan with national network
Pre-Tax Savings: HSA and FSAs for eligible expenses
Retirement: Competitive retirement package
Benefits eligible: Yes

Work Model, Schedule, and Status

Location: Rochester, MN (hybrid)
Hybrid requirements: Candidate must live within 100 miles of any Mayo Clinic site in Minnesota, Wisconsin, Florida, or Arizona.
On-site frequency: Purpose-driven on-site days; estimated average of approximately two days per quarter.
Schedule: Full Time (8 AM - 5 PM, Monday through Friday), with 1-week of on-call phone coverage approximately 1-2 weeks per year.
Exemption status: Exempt
Hours/Pay period: 80
Weekend schedule: N/A
International assignment: No

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Associate Data Engineer

CleanSlate Technology Group Austin, TX

Austin, TX

Today

Full time 3d Design Tools Amazon Web Services Artificial Intelligence

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Job Description

Austin, TX (onsite) Associate Data Engineer role supporting client data engineering work within CleanSlate Technology Group’s Data and AI Practice.

Responsibilities

Develop and maintain defined components of data pipelines and platform elements for analytics, machine learning, and AI workloads using established designs and guidance from experienced engineers.
Complete assigned data ingestion, transformation, and orchestration tasks using documented requirements, team review, and established patterns.
Support solution design and technical discussions by asking questions, documenting decisions, and completing follow-up tasks with guidance from senior team members.
Write clean, maintainable, and well-documented code aligned with team standards.
Execute assigned tests and data validation checks; document results and assist with deployment, monitoring, and troubleshooting of production data solutions under team guidance.
Escalate unexpected results and issues to the appropriate team member.
Collaborate with CSTG team members and client stakeholders by sharing task updates, documenting questions and requirements, and promptly raising blockers with the delivery team.
Participate in code reviews, design discussions, and agile team ceremonies; incorporate feedback and ask questions to strengthen understanding of team practices.
Follow engineering standards, patterns, and best practices.
Pursue ongoing learning and development in data engineering skills.

Requirements

Foundational hands-on experience building data pipelines, processing data, or working with data platforms via employment, internships, apprenticeships, coursework, or personal projects.
Foundational programming skills in Python, Java, or Scala, demonstrated through scripts or projects that process, transform, or move data.
Working knowledge of SQL, including filtering, joining, aggregating, and transforming data in relational tables.
Foundational understanding of data integration and pipeline concepts, with exposure to one or more: Spark, Databricks, Snowflake, Redshift, Azure Fabric, AWS Glue, or Azure Data Factory (not required to know all).
Familiarity with data modeling concepts and analytics-focused data structures.
Understanding of data quality concepts such as validation and consistency.
Foundational familiarity with AWS and/or Azure data services from hands-on projects, labs, coursework, internships, or professional experience.
Ability to collaborate effectively and communicate technical concepts clearly.

Technologies

Python
Java
Scala
SQL
Spark
Databricks
Snowflake
Redshift
Azure Fabric
AWS Glue
Azure Data Factory
AWS
Azure

Team and Role Overview

Cross-functional, highly collaborative teams combining CSTG consultants with client stakeholders to address complex data challenges.
Values engineers who are curious and pragmatic, with an interest in data engineering plus complementary understanding of AI and machine learning.
Role focuses on completing defined development, testing, and documentation tasks with guidance from experienced engineers.
Contributes to building and maintaining data pipelines and platform components for analytics, machine learning, and AI use cases.
Emphasizes execution, learning, and growth through clearly scoped assignments and feedback.
As experience grows, strengthens ability to complete defined pipeline tasks, validate data, troubleshoot common issues, and explain work with increasing independence.

Preferred Qualifications

AWS or Azure certifications; willingness to pursue certifications encouraged.
Databricks or Snowflake certifications; willingness to pursue certifications encouraged.
Exposure to agentic tooling like AWS Quick, Claude Work, Claude, Copilot, or OpenClaw.
Exposure to CI/CD pipelines or infrastructure-as-code concepts through projects, coursework, or professional experience.
Exposure to NoSQL databases or distributed data systems through coursework, labs, projects, or professional experience.
Exposure to AI-powered software development tools (such as Claude Code, Cursor, Kiro, or similar).
Exposure to consulting, client-facing work, or collaborative projects requiring communication of technical information to others.

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Staff Data Engineer

National Grid Syracuse, NY

Syracuse, NY

Today

$135k - $190k/yr Full time Data Data Architecture Data Engineer

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Job Description

National Grid is seeking a Staff Data Engineer to help make critical data available to business teams through end-to-end, high-quality pipelines. In this hybrid role, you will use agile practices to deliver rigorous engineering standards while also contributing to modernization efforts across data architecture, integrations, and streaming event processing.

As a Staff Data Engineer, you will play a hands-on role in building scalable solutions for data collection, storage, distribution, modeling, and analysis, and you will help shape how the organization prioritizes and plans technical work.

Job Purpose

Join the Data Engineering team focused on ensuring business teams at National Grid have access to critical data.
Use an agile framework to build end-to-end pipelines grounded in rigorous engineering standards and coding practices.
Contribute to modernization of architecture and tools to improve output, scalability, and speed.
Design and develop highly scalable, extensible data pipelines that support collection, storage, distribution, modeling, and analysis of large datasets from many channels.
Support an emphasis on data and data quality, with strong data warehousing and API integration experience.

Responsibilities

Own the assembly of architectural plans and project artifacts, serving as a driver of system architecture beyond individual team scope.
Execute on large organizational projects and break down work for yourself and others.
Integrate work across the organization by identifying edge cases and exception states.
Participate in architectural designs and provide software design expertise on and off the team.
Seek solutions that extend beyond immediate team needs by generalizing approaches to broader organizational problems where appropriate.
Understand and incorporate company-wide key technology frameworks, including occasional contribution to core engineering solutions.
Proactively anticipate what is next for the team and for the organization on the technical roadmap.
Drive the organization’s technical roadmap by participating in prioritization and planning.

Requirements

Lead the Data Engineering team to develop, test, document, and support scalable data pipelines.
Build new data integrations, including APIs, to support increases in data volume and complexity.
Establish and follow data governance processes and guidelines to ensure data availability, usability, consistency, integrity, and security.
Build and implement scalable solutions aligned with data governance standards and architectural roadmaps for integrations, storage, reporting, and analytics.
Collaborate with analytics and business teams to improve data models that feed business intelligence tools and support data-driven decision making.
Design and develop data integrations and a data quality framework.
Write unit, integration, and functional tests, and document work.
Design, implement, and automate deployment for a distributed system that collects and processes streaming events from multiple sources.
Perform data analysis to troubleshoot data-related issues and support resolution efforts.
Guide and mentor junior engineers on coding best practices and optimization.

Working Model and Location

Hybrid working model.
Based out of Waltham, MA or Brooklyn, NY office; hybrid work expectations are subject to business needs and company policy.
Location also listed as Syracuse, NY (hybrid).

Salary

Syracuse: USD 135,000 - 158,000 per year
Waltham: USD 151,000 - 177,000 per year
Brooklyn: USD 162,000 - 190,000 per year

Additional Information

National Grid will not provide visa sponsorship for this position now or in the future; you must be able to work without current or future visa sponsorship.
National Grid uses an assessment that evaluates job qualifications and characteristics using AI or statistically based scoring.
The role includes a career path with advancement opportunities within and across bands as experience and technical skills grow.
Candidates will be assessed and provided offers based on minimum qualifications and individual experience.

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Senior Data Engineer

NTT Ltd Charlotte, NC

Charlotte, NC

Today

Full time Senior Artificial Intelligence Data Engineer

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Job Description

The Senior Data Engineer role at NTT Ltd focuses on designing and optimizing scalable data pipelines with Databricks and related technologies to support AI-driven document processing. The position emphasizes structured extraction from unstructured and semi-structured documents, ontology-based modeling, and delivery of standardized JSON outputs for downstream underwriting workflows.

Key Responsibilities

Design, develop, and optimize scalable data pipelines using Databricks, Python, PySpark, and SQL.
Build ingestion, extraction, classification, validation, and transformation pipelines for documents including PDFs, emails, attachments, and Excel/XLSX files, as well as insurance applications and Statements of Values (SOVs).
Integrate LLMs and AI models into data-processing workflows to extract structured information from unstructured and semi-structured content.
Troubleshoot false positives, incorrect metadata, and inaccurate field values produced by LLM-based extraction pipelines.
Implement document classification, source-specific extraction rules, data validation, reconciliation, and quality-control mechanisms.
Transform extracted information into standardized JSON structures for downstream applications and underwriting workflows.
Design and implement ontology-based data models representing insurance entities, business concepts, and relationships.
Map extracted document attributes to standardized ontology concepts and metadata structures.
Optimize processing for large and complex Excel/XLSX and SOV files, including performance, scalability, and concurrency challenges.
Implement reliable data persistence using PostgreSQL, Lakebase, or related database technologies.
Develop and maintain APIs and data products to support downstream application integration.
Collaborate with brokerage, underwriting, AI, and data engineering teams to align extraction outputs with business requirements.
Monitor production pipelines, troubleshoot data-processing issues, and continuously improve reliability, performance, and data quality.

Required Qualifications

Minimum 7+ years of experience in data engineering, software development, or production data pipeline development.
Minimum 4+ years of hands-on experience with Databricks and scalable data-processing pipelines.
Minimum 5+ years of experience with Python, PySpark, and SQL.
Minimum 3+ years of experience processing unstructured and semi-structured data, including PDFs, emails, Excel files, JSON, and business documents.
Minimum 2+ years of experience integrating LLMs or AI models into document-processing or data-extraction pipelines.
Minimum 3+ years of experience implementing structured data extraction, document classification, validation, reconciliation, and data-quality controls.
Strong understanding of data modeling, schemas, metadata, entity relationships, and ontology or semantic modeling concepts.
Minimum 2+ years of experience designing JSON outputs, APIs, and data products for downstream consumption.
Minimum 2+ years of experience with PostgreSQL, Lakebase, or similar relational database technologies.
Minimum 2+ years of experience troubleshooting production performance, scalability, concurrency, and data-processing issues.
Strong understanding of cloud-based data architectures, distributed processing, and pipeline optimization.
Strong analytical, problem-solving, communication, and cross-functional collaboration skills.

Technologies

Databricks, Python, PySpark, SQL, LLMs, AI models, PostgreSQL, Lakebase, JSON, APIs, Excel/XLSX, PDFs, emails

Education

Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Engineering, or a related field, or equivalent.

Location

Charlotte, North Carolina, United States (onsite)

Travel

Nice to Have

Experience in insurance, commercial insurance, brokerage, underwriting, or risk management.
Experience processing insurance applications, Statements of Values (SOVs), policy documents, and underwriting submissions.
Experience with LLM frameworks, prompt engineering, structured outputs, and AI evaluation techniques.
Experience building custom ontologies, knowledge graphs, or semantic data layers.
Experience with document AI, OCR, information extraction, and document intelligence platforms.
Experience with Delta Lake, Lakehouse architecture, Databricks Workflows, and Delta Live Tables.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Experience optimizing large-scale document ingestion and distributed processing workloads.