Data Engineer

Role & responsibilities

We are seeking a highly motivated and technically strong Data Engineering Manager to lead our data engineering team and shape the data foundation of our organization. You will be responsible for architecting, building, and scaling robust data pipelines, storage systems, and real-time infrastructure to support analytics, product intelligence, and AI/ML use cases.

This is a hands-on leadership role requiring both technical expertise and people management skills to guide a growing team and ensure delivery of high-impact data solutions.

Key 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.

Preferred candidate profile

• Bachelors or Master’s 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.