Data Engineer

Essential Responsibilities & Duties

• Design, build, and maintain data pipelines that ingest, transform, and deliver enterprise data to AI solutions and business applications.
• Develop and manage integrations across enterprise data sources using APIs, Graph connectors, event-driven architectures, and batch/streaming patterns.
• Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns.
• Implement data quality, validation, and lineage controls to ensure accuracy and trustworthiness of data feeding AI workflows.
• Support and optimize data models underpinning Power BI dashboards and AI-enabled analytics.
• Collaborate with AI Engineers to define data contracts and ensure pipeline outputs meet solution requirements for schema, latency, and freshness.
• Instrument data pipelines for monitoring, alerting, cost control, and performance optimization.
• Implement data governance and security controls including access management, encryption, and compliance with organizational data policies.
• Identify data-related risks and support mitigation strategies in collaboration with architecture and platform teams.

• 4+ years of data engineering experience, with demonstrated ability to build and operate production data pipelines.
• Proficiency in Python and SQL; experience with PySpark or Spark is strongly preferred.
• Experience with Azure data services, including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and Azure SQL.
• Familiarity with Azure AI Search, Cosmos DB, or similar services used to support AI retrieval and storage patterns.
• Experience building and managing ETL/ELT pipelines with structured, semi-structured, and unstructured data sources.
• Knowledge of data modeling, schema design, and indexing strategies for both analytical and AI workloads.
• Familiarity with infrastructure-as-code and CI/CD practices for data pipeline deployment (e.g., Terraform, Azure Dev Ops).
• Knowledge of data governance principles, including data cataloging, lineage, access control, and privacy requirements.
• Knowledge of security best practices for data solutions, including encryption at rest and in transit, role-based access control, and private networking.
• Experience with Databricks, including Delta Lake and Unity Catalog, is a plus.
• Prior experience in professional services, engineering, or construction environments is a plus.
• Azure or Databricks certifications (e.g., Azure Data Engineer Associate, Azure Solutions Architect Expert, Databricks Data Engineer Professional) are a plus.

Work Environment

Functional Demands

Sedentary

Light

Medium

Other

Activity Level Throughout Workday

Occasional (0-35% of day)

Frequent (33-66% of day)

Continuous (67-100% of day)

Not Applicable

Sitting

Standing

Walking

Climbing

Lifting (floor to waist level)

Lifting (waist level and above)

Carrying objects

Push/pull

Twisting

Bending

Reaching forward

Reaching overhead

Squat/kneel/crawl

Wrist position deviation

Pinching/fine motor skills

Keyboard use/repetitive motion

Taste or smell (taste=never)

Talk or hear

Accurate 20/40

Very Accurate 20/20

Not Applicable

Near Vision

Far Vision

Yes

No

Not Applicable

Color Discrimination

Accurate

Not Applicable

Depth perception

Hearing

Environment Requirements

Occupational Exposure Risk Potential

Reasonably Anticipated

Not Anticipated

Blood borne pathogens

Chemical

Airborne communicable diseases

Extreme temperatures

Radiation

Uneven surfaces or elevations

Extreme noise levels

Dust/particulate matter

Other (exposure Risks)

Usual workday hours

8

10

12

Other work hours

GEI is an AA/equal opportunity employer, including disabled and veterans.