Data Engineering Manager - ETL/Data Warehousing

Overview : Data Engineering Manager for the Data Platform Team in Bangalore.

About HealthEdge :

HealthEdge is a healthcare SaaS software company that provides modern, disruptive digital healthcare solutions to health plans.

What you will do :

• Lead, mentor and grow a high-performing team of data engineers fostering a culture of technical excellence, collaboration and continuous improvement.

• Define and execute the technical roadmap for the data platform, aligning with broader engineering and product strategy.

• Design and build scalable, fault-tolerant data pipelines and ETL/ELT frameworks that support batch and real-time data processing at enterprise scale.

• Architect and evolve the data lakehouse, data warehouse and data integration layer using modern cloud-native technologies (e.g., AWS, Snowflake, Spark, Kafka, Airflow, dbt).

• Establish and enforce data governance, data quality and data security standards across all platform components.

• Partner with cross-functional stakeholders including product management, software engineering, analytics and data science teams to understand data needs and deliver solutions.

• Drive adoption of DataOps and engineering best practices including CI/CD for data, automated testing, monitoring, alerting and documentation.

• Manage sprint planning, backlog prioritization and delivery cadence for the data platform team.

• Evaluate, recommend and implement new tools, frameworks and technologies to keep the data platform current and competitive.

• Collaborate with leadership in Boston and Bangalore to align on priorities, timelines and resource planning.

• Recruit, hire, and develop a talented team of data and machine learning engineers.

• Mentor and coach team members to foster professional growth and innovation.

Qualifications :

• Bachelors or Masters degree in Computer Science, Engineering, Data Science or a related field.

• 10+ years of hands-on experience in data engineering, with at least 5 years in a people management role leading data platform or data infrastructure teams.

• Deep expertise in data warehousing, data modeling (dimensional and Data Vault), ETL/ELT design and big data technologies.

• Strong proficiency with cloud data platforms such as AWS (Redshift, Glue, S3, EMR, Lambda), Snowflake or Databricks.

• Experience with orchestration tools (Apache Airflow, Prefect or similar), streaming platforms (Kafka, Kinesis) and transformation frameworks (dbt, Spark).