EXL

Data Engineer

EXL · New Jersey, United States · $100K–$135K/yr

Business Consulting and Services · 10,001+ employees

4 h ago
Senior (5-10 yrs) Full-time United States
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About the role

Build and maintain scalable data pipelines, warehouses, and lakes to ensure accurate and secure data for analytics. Develop data ingestion, transformation, and integration capabilities while supporting data governance and platform optimization.

What they look for

SQL Python Spark AWS Databricks Azure Data modeling Data governance Metadata Distributed data Data pipelines Data warehousing Data lakes Data ingestion Data transformation Data integration

Requirements

Requires a minimum of 6 years of experience with strong proficiency in SQL, Python, and Spark. Candidates must have hands-on experience with cloud data platforms such as AWS or Azure and Databricks.

Benefits

Annual bonus

Full description

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.