Lead Data Engineer (Los Angeles, CA) • Experience: 9–12 years • Strong data engineering background • Databricks is a must, along with experience in data modeling, building pipelines, orchestration, and supporting reporting teams 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): • 8-12 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 Qualifications (Preferred): • 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.)