Data Engineer (3+ Years Experience)
Hybrid; Hartford, CT
$85,000- $105,000 plus bonus plus benefits
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 seeking a Data Engineer with 3+ years of experience in building and maintaining scalable data pipelines, ETL/ELT processes, and cloud-based data platforms. The ideal candidate will work closely with data analysts, data scientists, and business stakeholders to deliver high-quality, reliable, and accessible data for reporting, analytics, and AI/ML use cases.
- Bachelor''s degree in Computer Science, Information Technology, Engineering, or a related field.
- 3+ years of experience in Data Engineering or related roles.
- Strong proficiency in SQL and Python.
- Experience with ETL/ELT development and data pipeline orchestration.
- Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
- Experience working with data warehouses such as Snowflake, BigQuery, Redshift, or Synapse.
- Knowledge of Apache Spark/PySpark and workflow orchestration tools such as Airflow.
- Understanding of data modeling, data warehousing concepts, and performance tuning.
- Experience with Git, CI/CD, and Agile development methodologies.
- Design, develop, and maintain ETL/ELT pipelines for ingesting and processing large datasets.
- Build and optimize data workflows using Python, SQL, and distributed data processing frameworks.
- Develop and manage data models, data warehouses, and data lakes.
- Implement data quality checks, validation frameworks, and monitoring solutions.
- Integrate data from multiple structured and semi-structured sources.
- Collaborate with analysts, data scientists, and business teams to understand data requirements.
- Optimize query performance and ensure scalability of data solutions.
- Support CI/CD deployment, testing, and production monitoring of data pipelines.
- Document data lineage, architecture, and technical processes.
- Follow data governance, security, and compliance standards.
- Design, develop, and maintain ETL/ELT pipelines for ingesting and processing large datasets.
- Build and optimize data workflows using Python, SQL, and distributed data processing frameworks.
- Develop and manage data models, data warehouses, and data lakes.
- Implement data quality checks, validation frameworks, and monitoring solutions.
- Integrate data from multiple structured and semi-structured sources.
- Collaborate with analysts, data scientists, and business teams to understand data requirements.
- Optimize query performance and ensure scalability of data solutions.
- Support CI/CD deployment, testing, and production monitoring of data pipelines.
- Document data lineage, architecture, and technical processes.
- Follow data governance, security, and compliance standards.