We are looking for a Lead Data Engineer to build and maintain scalable data pipelines and data platforms that support analytics, business Intelligence, reporting, and AI. In this hands-on role, you will work closely with data architects, business stakeholders and analysts to develop reliable data solutions and ensure high-quality data is available across the organization. For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits
Salary Range: $93,900 - $154,200 Base annually
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.
ResponsibilitiesLead Data Engineering (Los Angeles)
Job Functions:
- Collaborate with client stakeholders to gather requirements, structure solutions, and ensure high‑quality, timely delivery.
- Experience working in the Databricks tech stack with strong proficiency in SQL, Python, and PySpark
- Design and optimize data models, data marts, and Lakehouse/warehouse layers with strong focus on medallion architecture, query optimization, and performance engineering.
- Build, orchestrate, and monitor scalable data pipelines on Databricks, ensuring reliable ingestion, transformation, CDC handling, and incremental load strategies.
- Manage end‑to‑end pipeline operations including performance tuning, data quality monitoring, alerting, and issue resolution across production workloads.
- Lead a project team of data engineers supporting multiple workstreams and provide technical leadership through code reviews, best‑practice guidance, reusable pattern creation, and mentorship to engineering team members.
- Prepare and maintain project documentation to support project execution and delivery.
Expected work split
- 50% Technical – Data modeling, hands-on coding, orchestration, and pipeline monitoring.
- 50% Management– Client Collaboration, requirements gathering, designing technical solutions, presentations, global team management and mentoring.
Qualifications (Required):
- 6-8 years’ experience in data engineering and analytics roles
- Bachelor’s or Master's degree in analytics, computer science/engineering, economics, mathematics, or related areas.
- Experience building and maintaining ETL/ELT pipelines
- Solid understanding of data warehousing concepts and dimensional data modeling
- Familiarity with workflow orchestration tools such as Airflow or similar
- Experience working with cloud data platforms or modern data infrastructure
- Entrepreneurial hands-on approach to work. Demonstrated leadership ability and willingness to take initiative
- Superior analytical and problem solving skills
- Outstanding written and verbal communication skills
- Effective time management and attention to detail
- Hands on experience in using SQL, Python and Workflow Schedulers (Apache Airflow, Cron)
- Experience in leading team and coordinating with internal / external stakeholders
- Experience in using Cloud Platforms (AWS / GCP / Azure)
- Experience in using Visualization tools (Tableau / Power BI)
- Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)
- Collaborate with client stakeholders to gather requirements, structure solutions, and ensure high‑quality, timely delivery.
- Experience working in the Databricks tech stack with strong proficiency in SQL, Python, and PySpark
- Design and optimize data models, data marts, and Lakehouse/warehouse layers with strong focus on medallion architecture, query optimization, and performance engineering.
- Build, orchestrate, and monitor scalable data pipelines on Databricks, ensuring reliable ingestion, transformation, CDC handling, and incremental load strategies.
- Manage end‑to‑end pipeline operations including performance tuning, data quality monitoring, alerting, and issue resolution across production workloads.
- Lead a project team of data engineers supporting multiple workstreams and provide technical leadership through code reviews, best‑practice guidance, reusable pattern creation, and mentorship to engineering team members.
- Prepare and maintain project documentation to support project execution and delivery.
Work Split
- 50% Technical – Data modeling, hands-on coding, orchestration, and pipeline monitoring.
- 50% Management– Client Collaboration, requirements gathering, designing technical solutions, presentations, global team management and mentoring.
Skills Required
- 6-8 years' experience in data engineering and analytics roles
- Bachelor's or Master's degree in analytics, computer science/engineering, economics, mathematics, or related areas
- Experience building and maintaining ETL/ELT pipelines
- Solid understanding of data warehousing concepts and dimensional data modeling
- Familiarity with workflow orchestration tools such as Airflow or similar
- Experience working with cloud data platforms or modern data infrastructure
- Hands on experience in using SQL, Python and Workflow Schedulers (Apache Airflow, Cron)
- Experience working in the Databricks tech stack with strong proficiency in PySpark
- Experience in using Cloud Platforms (AWS / GCP / Azure)
- Experience in using Visualization tools (Tableau / Power BI)
- Experience with Big Data Technologies (Hadoop, Hive, HBase, Pig, Spark, etc.)
- Experience in leading team and coordinating with internal / external stakeholders
- Entrepreneurial hands-on approach, demonstrated leadership, strong analytical and communication skills
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
