Azure Data Engineer Databricks & Data Factory

Be Part Of A High-Performing Team:

Join the technology organization of a global financial institution known for disciplined risk management, long-term client relationships, and continued investment in modern data capabilities. This role supports a compliance technology group responsible for delivering trusted, scalable data solutions in a highly regulated environment. The team is building modern ingestion, transformation, and storage capabilities that improve access to reliable metrics and support the onboarding of new enterprise datasets.

What s In Store For You:

Engagement: W2 only (no C2C/1099)

This hybrid opportunity offers the chance to contribute to a visible data modernization initiative while working with Azure cloud technologies, Databricks, and enterprise data platforms. The position provides hands-on exposure to complex financial-services data, compliance technology, scalable pipeline development, and data quality practices within a collaborative technical environment.

How You Will Make An Impact:

• Design and develop scalable data ingestion, transformation, and storage pipelines.
  
• Build and maintain ETL and ELT workflows using Azure Data Factory, Python, and SQL.
  
• Process data across Databricks Medallion Architecture layers, including staging, curated, and consumption-ready datasets.
  
• Support the development and enhancement of a centralized metrics repository.
  
• Onboard new datasets while ensuring accuracy, completeness, consistency, and traceability.
  
• Optimize data storage, transformation logic, and pipeline performance for large-volume processing.
  
• Troubleshoot data issues and collaborate with technical and business stakeholders to deliver reliable data products.
  
• Apply data quality controls and development standards appropriate for a regulated financial environment.
  

Do you bring proven success in Azure data engineering and scalable ETL development?

• 5 7 years of relevant experience in data engineering, data integration, ETL development, or a comparable technical discipline.
  
• Strong hands-on programming experience with Python.
  
• Advanced SQL skills, including complex queries, data transformations, performance tuning, and relational data structures.
  
• Practical experience designing and supporting ETL or ELT pipelines with Azure Data Factory.
  
• Experience working with Azure Databricks and layered data architectures, preferably the Medallion Architecture.
  
• Knowledge of SQL Server, staging environments, data repositories, and enterprise storage solutions.
  
• Demonstrated ability to validate data quality and resolve ingestion, transformation, and reconciliation issues.
  
• Experience building scalable pipelines that process large volumes of structured or semi-structured data.
  
• Strong analytical, troubleshooting, documentation, and communication skills.
  
• Ability to work effectively in a hybrid environment and collaborate across technical and business teams.