Data Engineering Manager

Role Overview: As a Data Engineering Manager at our Hyderabad office, you will be responsible for leading a team dedicated to designing, building, and operating scalable data infrastructure and pipelines for the Care Solutions platform. Your role will involve collaborating with Engineering, Analytics, Product, and BI teams to ensure reliable and insight-ready data for our business and clients. Key Responsibilities: - Lead the design, development, and operation of secure and high-performance data pipelines and infrastructure on AWS - Own and prioritize the data engineering roadmap, focusing on strategic platform investments and near-term delivery priorities - Architect end-to-end data workflows including ingestion, transformation, storage, and delivery to support internal analytics and client-facing product capabilities - Collaborate with BI, Analytics, and Data Science teams to model and deliver trusted datasets - Establish and enforce data quality, governance, and lineage practices - Drive adoption of modern data engineering practices like CI/CD, Infrastructure as Code, and observability - Champion migration and modernization initiatives for a cloud-native data platform on AWS - Ensure compliance with healthcare data regulations and implement security best practices - Proactively identify and address data reliability issues, performance bottlenecks, and technical debt - Promote the use of AI in the software development lifecycle for intelligent code generation, testing, pipeline monitoring, anomaly detection, and predictive data quality Qualifications Required: - Degree in Computer Science, Engineering, Statistics, or related field - Minimum 12 years of technical experience with 3+ years managing data engineering teams - 5+ years of hands-on experience as a data engineer, focusing on building production-grade data pipelines - Deep expertise in AWS data services such as S3, Glue, Redshift, Athena, etc. - Experience with MongoDB, ETL/ELT frameworks, workflow orchestration tools, data warehousing, and data lake architectures - Familiarity with streaming and batch data processing frameworks, data quality, observability, and data catalog tools - Knowledge of Infrastructure as Code for data platform components, CI/CD practices, and relational databases - Strong understanding of data governance, security controls, and compliance frameworks Additional Details: The company values individuals who can thrive in a fast-paced environment, communicate complex data concepts effectively, automate processes, accept feedback gracefully, and create psychologically safe environments for their team. Role Overview: As a Data Engineering Manager at our Hyderabad office, you will be responsible for leading a team dedicated to designing, building, and operating scalable data infrastructure and pipelines for the Care Solutions platform. Your role will involve collaborating with Engineering, Analytics, Product, and BI teams to ensure reliable and insight-ready data for our business and clients. Key Responsibilities: - Lead the design, development, and operation of secure and high-performance data pipelines and infrastructure on AWS - Own and prioritize the data engineering roadmap, focusing on strategic platform investments and near-term delivery priorities - Architect end-to-end data workflows including ingestion, transformation, storage, and delivery to support internal analytics and client-facing product capabilities - Collaborate with BI, Analytics, and Data Science teams to model and deliver trusted datasets - Establish and enforce data quality, governance, and lineage practices - Drive adoption of modern data engineering practices like CI/CD, Infrastructure as Code, and observability - Champion migration and modernization initiatives for a cloud-native data platform on AWS - Ensure compliance with healthcare data regulations and implement security best practices - Proactively identify and address data reliability issues, performance bottlenecks, and technical debt - Promote the use of AI in the software development lifecycle for intelligent code generation, testing, pipeline monitoring, anomaly detection, and predictive data quality Qualifications Required: - Degree in Computer Science, Engineering, Statistics, or related field - Minimum 12 years of technical experience with 3+ years managing data engineering teams - 5+ years of hands-on experience as a data engineer, focusing on building production-grade data pipelines - Deep expertise in AWS data services such as S3, Glue, Redshift, Athena, etc. - Experience with MongoDB, ETL/ELT frameworks, workflow orchestration tools, data warehousing, and data lake architectures - Familiarity with streaming and batch data processing frameworks, data quality, observability, and data catalog tools - Knowledge of Infrastructure as Code for data platform components, CI/CD practices, and relational databases - Strong understanding of data governance, security controls, and compliance fra