Data Engineering Manager

Role & responsibilities

• Lead and manage the Data Engineering team responsible for building and maintaining scalable data platforms and pipelines.
• Define data engineering strategy, architecture, standards, and technology roadmaps aligned with business objectives.
• Oversee the design, development, testing, deployment, and maintenance of batch and real-time data pipelines.
• Drive development of data lakes, data warehouses, lakehouse platforms, and cloud-based data solutions.
• Collaborate with Data Science, Analytics, Product, Engineering, and Business teams to deliver reliable and accessible data.
• Ensure data pipelines and platforms meet requirements for scalability, availability, performance, security, and cost efficiency.
• Establish best practices for data quality, governance, observability, documentation, and operational reliability.
• Lead cloud migration, platform modernization, and data transformation initiatives.
• Manage technical priorities, project timelines, resources, budgets, and delivery commitments.
• Identify and resolve complex data engineering, architecture, performance, and production issues.
• Mentor and develop data engineers while building a high-performing engineering culture.
• Evaluate new technologies and drive automation, CI/CD, and engineering productivity improvements.
• Communicate technical strategy, project status, risks, and business impact to senior leadership.

Preferred candidate profile

• 5 to 10 years of experience in Data Engineering, Data Platform Engineering, or a related technology field, including experience leading teams or major initiatives.
• Strong hands-on expertise in SQL and Python, Java, or Scala.
• Proven experience designing and managing large-scale ETL/ELT pipelines and distributed data processing systems.
• Strong knowledge of Apache Spark, Kafka, Airflow, Databricks, Snowflake, or equivalent technologies.
• Experience with at least one major cloud platform such as AWS, Azure, or GCP.
• Strong understanding of data warehousing, data lakes, lakehouse architecture, data modelling, and distributed systems.
• Experience implementing data quality, governance, security, monitoring, and observability practices.
• Knowledge of CI/CD, DevOps, Infrastructure as Code, and cloud-native engineering practices.
• Strong system design, troubleshooting, performance optimization, and problem-solving skills.
• Demonstrated ability to lead, mentor, and manage data engineering teams.
• Excellent stakeholder management, communication, prioritization, and project management skills.
• Ability to balance hands-on technical leadership with people management and strategic planning.
• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical discipline.
• Master's degree or relevant cloud/data engineering certifications is an added advantage.