Data Engineer
EXL United States · $80K–$95K/yr
Business Consulting and Services · 10,001+ employees
About the role
The Data Engineer will build, optimize, and maintain scalable data platforms and pipelines. They will collaborate with data scientists and business teams to ensure high-quality data delivery for analytics and reporting.
What they look for
Requirements
Candidates must have 3-4 years of experience in data science or analysis and a degree in a related field. Proficiency in Python, SQL, and Google Cloud Platform services is required.
Benefits
Full description
Data Engineer Hybrid; Jersey City, NJ $80k-$95k plus bonus and benefits EEO/Minorities/Females/Vets/Disabilities
For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits
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.
We are looking for a skilled Data Engineer with strong experience in building, optimizing, and maintaining scalable data platforms and pipelines. The ideal candidate will work closely with data scientists, analysts, and business teams to ensure reliable, high-quality data delivery across analytics and reporting use cases.
Key Skills & Technologies
- Strong programming experience in Python and SQL
- Hands-on experience with Google Cloud Platform (GCP) services
- Expertise in BigQuery for data warehousing, performance tuning, and cost optimization
- Experience with ETL/ELT frameworks and large-scale data pipeline development
- Workflow orchestration using Apache Airflow
- CI/CD implementation for data pipelines using tools like Git, Jenkins, or Cloud Build
- Solid understanding of data modeling, partitioning, and schema design
- Experience with cloud storage, data validation, and monitoring
- Knowledge of containerization (Docker) and basic DevOps practices is a plus
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