Senior Azure Data Engineer

Eliassen Group; United States; Remote; USD 103,000 - 117,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401k with company matching

Life insurance

Job summary

Eliassen Group is seeking a Senior Azure Data Engineer for a remote contract-to-hire engagement in the United States. You will migrate data from on-prem Oracle/DataStage to an Azure data lake using Databricks and Data Factory, and shape the data architecture with medallion patterns.

You will design, build, and optimize data pipelines, champion data quality, and guide engineering best practices while collaborating with cross-functional teams. W2 benefits apply upon conversion to FTE.

Qualifications

• Extensive hands-on data engineering experience in enterprise environments.
• Proficiency with Azure Databricks and Azure Data Factory.
• Strong SQL and Python/PySpark development skills.
• Experience designing batch data pipelines and ETL/ELT workflows.
• Knowledge of medallion/lakehouse architectures (Bronze-Silver-Gold).
• Experience with relational databases and large datasets.
• Understanding of data modeling, partitioning, and performance optimization.
• Git or similar version-control experience; CI/CD familiarity.
• Ability to guide and mentor teammates; strong communication.

Responsibilities

• Design, develop, test, and maintain data pipelines using Azure Databricks and Azure Data Factory.
• Support migration of data and ETL workloads to an Azure cloud data lake.
• Develop scalable ingestion, transformation, and data-processing solutions.
• Design and implement medallion architecture patterns across data layers.
• Build data-quality checks, reconciliation, and validation into pipelines.
• Automate validation and testing to improve data reliability.
• Guide technical discussions on data architecture, design, and standards.
• Troubleshoot pipeline failures and performance issues.
• Collaborate with engineers, analysts, and stakeholders to translate requirements.
• Participate in code reviews, documentation, testing, deployment, and improvement initiatives.
• Promote reusable development patterns and engineering best practices.

Skills

Azure Databricks

Azure Data Factory

SQL

Python/PySpark

Data modeling

ETL/ELT design

Data quality

Medallion architecture

Data lakehouse

Git

CI/CD

Troubleshooting

Communication

Tools

Databricks

Azure DevOps

Delta Lake

IBM DataStage

Oracle

Job description

Description:

Remote

As a Senior Azure Data Engineer, you will help modernize an enterprise data platform by migrating data and workloads from an on-premises Oracle data warehouse and IBM DataStage environment to a cloud-based Azure data lake architecture. You will design, build, and optimize scalable data pipelines using Azure Databricks and Azure Data Factory. This role requires someone who can contribute directly to development while also helping guide data architecture decisions, technical design discussions, and engineering best practices. Your work will include ingesting data from legacy and enterprise source systems, implementing data-quality and validation processes, and promoting data through medallion architecture layers. You will collaborate with engineers, architects, analysts, and business partners to build reliable, maintainable, and trusted data products. Healthcare or health-plan experience is beneficial, particularly experience with claims, billing, finance, or plan-administration data, but strong Azure Databricks and data-platform engineering capabilities are the primary priorities.

This is a contract to hire opportunity. Applicants must be willing and able to work on a w2 basis and convert to FTE following contract duration. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $75.00 to $85.00/hr. w2

Responsibilities

• Design, develop, test, and maintain data pipelines using Azure Databricks and Azure Data Factory.
• Support the migration of data and ETL workloads from an on-premises Oracle and DataStage environment to an Azure cloud data lake.
• Develop scalable ingestion, transformation, and data-processing solutions.
• Design and implement medallion architecture patterns across Bronze, Silver, and Gold data layers.
• Build data-quality, reconciliation, and validation checks directly into data pipelines and engineering workflows.
• Automate validation and testing to improve the reliability of data products.
• Help guide technical discussions and decisions related to data architecture, solution design, and engineering standards.
• Troubleshoot pipeline failures, data-quality issues, and performance problems.
• Collaborate with engineers, analysts, architects, and business stakeholders to translate requirements into practical data solutions.
• Participate in code reviews, documentation, testing, deployment, and continuous-improvement activities.
• Promote reusable development patterns and sound engineering practices across the team.

Experience Requirements

• Strong hands-on data engineering experience in enterprise environments.
• Demonstrated experience with Azure Databricks and Azure Data Factory.
• Strong SQL and Python or PySpark development skills.
• Experience designing and developing batch data pipelines and ETL or ELT workflows.
• Experience implementing data-quality, data-validation, and reconciliation processes.
• Knowledge of medallion or lakehouse architecture, including Bronze, Silver, and Gold data layers.
• Experience working with relational databases and large, complex datasets.
• Understanding of data modeling, schema design, partitioning, and performance optimization.
• Experience with Git or another version-control platform.
• Experience working with CI/CD and automated deployment practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to contribute directly to development while providing technical guidance to other team members.
• Strong communication and collaboration skills.
• Preferred: experience migrating on-premises platforms to Azure, Oracle and IBM DataStage, Azure data lake or lakehouse design, Delta Lake and Databricks features, automated data testing and monitoring, Azure DevOps, Agile or Scrum, healthcare or finance-related data, and regulated enterprise environments.