Principal Data Engineer

Role & responsibilities

• Lead and mentor a team of data engineers to design, develop, and maintain high-performance data pipelines and platforms.
• Architect scalable ETL/ELT processes, streaming pipelines, and data lake/warehouse solutions (e.g., Redshift, Snowflake, BigQuery).
• Own the roadmap and technical vision for the data engineering function, ensuring best practices in data modeling, governance, quality, and security.
• Drive adoption of modern data stack tools (e.g., Airflow, Kafka, Spark etc.) and foster a culture of continuous improvement.
• Ensure the platform is reliable, scalable, and cost-effective across batch and real-time use cases.
• Champion data observability, lineage, and privacy initiatives to ensure trust in data across the org.

Required Qualification

• Bachelors or Masters degree in Computer Science, Engineering, or related technical field.
• 8+ years of hands-on experience in data engineering with at least 2+ years in a leadership or managerial role.
• Proven experience with distributed data processing frameworks such as Apache Spark, Flink, or Kafka.
• Strong SQL skills and experience in data modeling, data warehousing, and schema design.
• Proficiency with cloud platforms (AWS/GCP/Azure) and their native data services (e.g., AWS Glue, Redshift, EMR, BigQuery).
• Solid grasp of data architecture, system design, and performance optimization at scale.
• Experience working in an agile development environment and managing sprint-based delivery cycles.