HealthEdge - Data Engineering Manager - ETL in Bangalore, भारत

Job Description : Role : Data Engineering https://jobeax.com/link/Y4Vh9H1078tPWNuB Platform Team | Bangalore, https://jobeax.com/link/ohUVt2NrqGW1HgSp HealthEdge :HealthEdge is a healthcare SaaS software company that provides modern, disruptive digital healthcare solutions to health https://jobeax.com/link/sgJ64uZ8xYc3yAYe integrated platform - including HealthRules Payer, GuidingCare, HealthEdge Source and Wellframe - enables health plans to modernize their core systems, optimize operations and improve member https://jobeax.com/link/N4pMsOQUytFzzHPr are committed to building the future of healthcare through innovation, empathy and https://jobeax.com/link/mQfrrzEM2y1HDePW the Role :We are looking for an experienced and passionate Data Engineering Manager to lead and grow the Data Platform team based in https://jobeax.com/link/QZP3gVWw16NxJIzV 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 https://jobeax.com/link/7BB5Cz4KjBeQ3bW2 will manage a team of data engineers while collaborating closely with product, engineering and other stakeholders to deliver high-impact data https://jobeax.com/link/XnflZD2dGSZYgXFG 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.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). (ref:hirist.tech)