Lead Data Engineer

Build and maintain scalable data pipelines and data platforms that support analytics, business Intelligence, reporting, and AI. Work closely with data architects, business stakeholders and analysts to develop reliable data solutions and ensure high-quality data is available across the organization. Collaborate with client stakeholders to gather requirements, structure solutions, and ensure high‑quality, timely delivery. 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. Requirements 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.) #J-18808-Ljbffr