Sr. Feature Engineer

Work Location: Pittsburgh
Work Mode      : Onsite
Pay Range       :$110K-$125K /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 https://www.exlservice.com/us-careers-and-benefits

Job Summary:

We are looking for an experienced Lead Data Engineer to drive the design and delivery of scalable data platforms and pipelines. This role requires strong expertise in Python, SQL, and modern data engineering practices, along with the ability to lead teams, define standards, and implement DevOps-driven data workflows.

Key Responsibilities:

• Lead the design and implementation of scalable ETL/ELT pipelines and data architecture
• Define best practices and standards for data engineering, code quality, and performance optimization
• Own end-to-end delivery of data pipelines, ensuring reliability, scalability, and maintainability
• Build and optimize frameworks for data ingestion, transformation, and processing of large datasets
• Drive implementation of CI/CD and DevOps practices across data engineering workflows
• Oversee automation for data pipeline deployment, monitoring, and alerting
• Collaborate with business and technology stakeholders to translate requirements into scalable solutions
• Mentor and guide junior engineers; conduct code reviews and provide technical leadership
• Lead troubleshooting, root cause analysis, and performance tuning across data platforms

Must-Have Skills:

• Strong hands-on experience in Python and SQL with the ability to guide others
• Deep understanding of data engineering concepts (ETL/ELT, data modeling, warehousing)
• Proven experience designing and leading production-grade data pipelines and platforms
• Strong exposure to DevOps practices and tools (Git, CI/CD pipelines, Jenkins, Docker)
• Experience with system design, scalability, and performance optimization
• Strong problem-solving skills with ownership mindset

Good to Have:

• Experience with PySpark or large-scale data processing frameworks
• Exposure to cloud data platforms (AWS, Azure, or GCP)
• Experience with workflow orchestration tools (e.g., Airflow)
• Understanding of data governance, data quality, and lineage frameworks

Key Responsibilities:

• Strong hands-on experience in Python and SQL with the ability to guide others
• Deep understanding of data engineering concepts (ETL/ELT, data modeling, warehousing)
• Proven experience designing and leading production-grade data pipelines and platforms
• Strong exposure to DevOps practices and tools (Git, CI/CD pipelines, Jenkins, Docker)
• Experience with system design, scalability, and performance optimization
• Strong problem-solving skills with ownership mindset