Data BAU Lead – Data Engineering
Summary
Lead a team to maintain and improve cloud-based data pipelines, warehouses, and lakes, migrating legacy systems to Snowflake and AWS Glue/Spark while ensuring stability and data quality.
We are looking for an experienced Data BAU Lead to lead data engineering operations, production support, and continuous improvement in a cloud-first environment.
Key Responsibilities
- Lead a team of data engineers managing BAU operations, production support, incidents, and platform stability.
- Design, develop, and support scalable data pipelines, data feeds, data lakes, and data warehouses.
- Drive migration of legacy Oracle, MS-SQL, Hive, and Impala workloads to Snowflake, Spark, and AWS Glue.
- Work closely with business, architects, data scientists, and DevOps teams to deliver data solutions.
- Improve data quality, performance, monitoring, automation, and operational efficiency.
- Support data strategy, architecture, security, and governance initiatives.
Key Skills & Experience
- 7+ years of data engineering experience, including 2+ years in hands-on lead/production support roles.
- Strong expertise in AWS – S3, Glue, DMS, MWAA/Airflow, IAM, Lambda, RDS, Kinesis, and Step Functions.
- Strong Snowflake expertise and data warehouse/data lake experience.
- Hands-on programming skills in SQL, Python, PySpark, Spark, and Unix Shell.
- Experience with ETL, data ingestion, data integration, distributed systems, and large-scale datasets.
- Strong understanding of CI/CD, Git, Agile/SDLC, and cloud optimization.
- Proven experience in team leadership, stakeholder management, and production/BAU environments.
Bachelor’s degree in
Computer Science, Engineering, STEM, or related field