Manager Data Platform Engineer

Location: Bangalore, UNAVAILABLE, IN

Employment Type: FULL_TIME

Overview

JOB DESCRIPTION 

Data Engineering Manager 

Data Platform Team | Bangalore, India 

 

About HealthEdge 

HealthEdge® is a healthcare SaaS software company that provides modern, disruptive digital healthcare solutions to health plans. Our integrated platform – including HealthRules® Payer, GuidingCare®, HealthEdge Source™ and Wellframe™ – enables health plans to modernize their core systems, optimize operations and improve member outcomes. We are committed to building the future of healthcare through innovation, empathy and trust. 

About the Role 

We are looking for an experienced and passionate Data Engineering Manager to lead and grow the Data Platform team based in Bangalore. In this role, you will own the strategy, architecture and execution of our enterprise data platform, enabling reliable, scalable and secure data pipelines that power analytics, reporting and AI/ML initiatives across the organization. You will manage a team of data engineers while collaborating closely with product, engineering and other stakeholders to deliver high-impact data solutions. 

Key Responsibilities 

• 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. 

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Qualifications 

Required 

• Bachelor’s or Master’s 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).