Azure Data Engineer Databricks & Data Factory

Zohorecruit; Jersey City (NJ); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Axiom Path is leading an AI-first recruiting and staffing initiative, delivering data solutions across the financial services sector. This role focuses on building scalable ingestion, transformation, and storage pipelines in a regulated environment.

The candidate will work with Azure Data Factory, Python, SQL, and Databricks to implement Medallion Architecture, enhance a centralized metrics repository, and onboard new datasets while ensuring data quality and traceability.

Qualifications

• 5-7 years of data engineering experience.
• Proficient in Python and SQL.
• Experience with Azure Data Factory.
• Experience with Azure Databricks and Medallion Architecture.
• Knowledge of data quality controls and data governance.

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 (staging, curated, consumption-ready).
• Support the development and enhancement of a centralized metrics repository.
• Onboard new datasets ensuring accuracy, completeness, consistency and traceability.
• Optimize data storage, transformation logic, and pipeline performance for large volumes.
• Troubleshoot data issues and collaborate with stakeholders to deliver reliable data products.
• Apply data quality controls and development standards for a regulated environment.

Skills

Azure data engineering

ETL development

Python

SQL

Azure Data Factory

Azure Databricks

Medallion Architecture

Data quality controls

Tools

Azure Data Factory

Azure Databricks

SQL Server

Job description

Jersey City, United States | Posted on 07/21/2026

Axiom Path is an AI-first recruiting and staffing firm delivering RPO, MSP, and direct-hire solutions to enterprise clients across the U.S. Our team of experienced recruiters, supported by purpose-built automation, moves faster and communicates better so clients get qualified talent sooner and candidates get a clear, responsive process from first contact to start date.

Job Description

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.
  

Requirements

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.