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).

- Solid understanding of data governance, metadata management, data cataloging and data quality frameworks.

- Familiarity with BI & dashboarding tools and multi-dimensional modeling.

- Great problem-solving capabilities, troubleshooting data issues and experience in stabilizing big data systems.

- Excellent communication skills with the ability to translate technical concepts for non-technical stakeholders.

- Demonstrated ability to hire, develop and retain top engineering talent.

Preferred :

- Experience in the healthcare or health insurance domain, with familiarity with claims, enrollment and care management data.

- Hands-on experience with ML feature stores, data mesh architectures or real-time analytics platforms.

- Knowledge of HIPAA, PHI handling requirements and healthcare data security standards.

- Experience working in a globally distributed engineering organization.

- Familiarity with infrastructure-as-code (Terraform, CloudFormation) and containerized environments (Docker, Kubernetes).