Azure Data Engineer Databricks & Data Factory

Axiom Path • Jersey City, NJ

1d • Hybrid

About The Position

Join the technology organization of a global financial institution, supporting a compliance technology group that delivers trusted, scalable data solutions in a highly regulated environment. The team is developing modern ingestion, transformation, and storage capabilities to improve access to reliable metrics and onboard new enterprise datasets.

This hybrid opportunity contributes to a visible data modernization initiative using Azure cloud technologies, Databricks, and enterprise data platforms. The role offers hands-on work with financial-services data, compliance technology, scalable pipeline development, and data quality practices in a collaborative technical environment. Engagement is W2 only; C2C and 1099 are not accepted.

Requirements

• 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; Medallion Architecture is preferred.
• Knowledge of SQL Server, staging environments, data repositories, and enterprise storage solutions.
• 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.

Nice To Haves

• Experience with the Medallion Architecture.

Responsibilities

• 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 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed