Data Engineer

Work Location: Whippany, NJ
Work Mode: Hybrid (Minimum 2 days/week in office)
Salary Range: $100K/Yr - $135K/Yr Base + Annual Bonus

The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process

For more information on benefits and what we offer please visit us at US Careers and Benefits

Build and maintain scalable data pipelines, warehouses, and lakes to ensure accurate, accessible, and secure data for analytics and reporting. Develop data ingestion, transformation, integration, and data quality capabilities.

Support data governance, monitoring, reconciliation, and platform optimization.

Build and maintain scalable data pipelines, warehouses, and lakes to ensure accurate, accessible, and secure data for analytics and reporting. Develop data ingestion, transformation, integration, and data quality capabilities.

Support data governance, monitoring, reconciliation, and platform optimization.

Key Responsibilities:

·                Develop and optimise data pipelines and ETL/ELT processes.

·                Build and maintain data warehouse and data lake structures.

·                Ensure data quality, governance, and security across platforms.

·                Collaborate with data scientists and engineering teams.

·                Monitor performance and troubleshoot data workflows.

• Minimum 6 years of experience
• Strong SQL, Python, Spark.
• Python expertise (mandatory) and hands-on experience with AWS services and/or Databricks.
• Experience with cloud data platforms AWS and/or Azure.
• Knowledge of data modelling, governance, and metadata.
• Understanding of large-scale distributed data