Azure Data Engineer

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.