Data Engineering Manager

Overview:

Data Engineering Manager

We are seeking an experienced Data Engineering Manager in our Hyderabad office to lead a team responsible for designing, building, and operating the scalable data infrastructure and pipelines that power the Care Solutions platform, and for partnering with customers, Engineering, Analytics, Product, and BI teams to ensure reliable, insight-ready data across our business and clients.

Areas of Responsibility

Data Engineering Leadership

Lead the design, development, and operation of scalable, secure, and high-performance data pipelines and data infrastructure on AWS

Own the data engineering roadmap, balancing strategic platform investments with near-term delivery priorities

Architect end-to-end data workflowsincluding ingestion, transformation (ETL/ELT), storage, and delivery, supporting both internal analytics and client-facing product capabilities

Partner with BI, Analytics, and Data Science teams to model and deliver trusted, well documented datasets

Establish and enforce data quality, data governance, and data lineage practices across the platform

Drive adoption of modern data engineering practices including CI/CD for data pipelines, Infrastructure as Code, and observability

Champion migration and modernization initiatives, including cloud-native data platform evolution on AWS (e.g., Redshift, Glue, Lake Formation, S3)

Ensure compliance with HIPAA and other healthcare data regulations; implement security best practices for data at rest and in transit

Proactively identify and remediate data reliability issues, performance bottlenecks, and technical debt

Champion the use of AI throughout the software development lifecycle from intelligent code generation and automated testing to AI-assisted pipeline monitoring, anomaly detection, and predictive data quality

Build a High-Performing Team

Recruit, mentor, and develop data engineers across data pipeline engineering and data modeling

Create individualized career growth plans aligned with both team needs and individual aspirations

Foster a culture of engineering excellence, data ownership, and continuous improvement

Provide regular coaching and feedback to help engineers grow their technical and leadership capabilities

Retain and reward high-performing team members

Promote knowledge sharing, documentation, and internal best practices

Build effective on-call and incident management practices for production data systems

Source and hire engineers who embody HealthEdge's core values

Comfortable leading remote and distributed teams

Project and Delivery Management

Plan, prioritize, and manage project timelines, ensuring on-time delivery of features and integrations

Break down complex initiatives into manageable tasks and milestones with clear ownership

Coordinate with product managers to translate business requirements into technical roadmaps

Manage dependencies and risks across multiple workstreams, escalating proactively when needed

Establish and track engineering metrics (velocity, quality, uptime) to drive continuous improvement

Ensure delivery-focused execution while maintaining quality and compliance standards

Collaborate effectively with US based teams across time zones.

Required Skills and Experience

Degree in Computer Science, Engineering, Statistics, or a related field

Minimum 12 years of progressive technical experience, including 3+ years managing data engineering teams

5+ years of hands-on experience as a data engineer, with proven expertise in building production-grade data pipelines

Deep expertise in AWS data services (e.g., S3, Glue, EMR, Redshift, Athena, Lake Formation, Step Functions)

Experience with MongoDB including schema design, querying, and integration with data pipelines

Hands-on experience with ETL/ELT frameworks and workflow orchestration tools (Apache Airflow, AWS Glue, dbt, or similar)

Experience with data warehousing concepts, dimensional modeling, and data lake/lakehouse architectures

Familiarity with streaming and batch data processing frameworks (Apache Spark, Kafka, Kinesis, or similar)

Knowledge of data quality, data observability, and data catalog tooling

Experience with Infrastructure as Code (Terraform, CloudFormation, or AWS CDK) for data platform components

Familiarity with CI/CD practices applied to data pipelines and data platform deployments

Experience with relational databases (MS SQL Server, PostgreSQL) and high-availability configurations

Proven track record of leading complex data platform migrations or modernization programs

Strong understanding of data governance, security controls, and compliance frameworks

Preferred Skills and Experience

Healthcare technology experience with deep understanding of HIPAA and data standards (HL7, FHIR)

Experience with AWS DynamoDB or AWS DocumentDB as migration targets or complementary NoSQL solutions

Hands-on experience with BI and visualization platforms (AWS Quicksight, Tableau, Power BI, or similar)

Behaviors & Traits

Ability to thrive in a fast-paced, dynamic environment with competing priorities

Excellent communication skills with ability to translate complex data concepts for non-technical stakeholders

Bias toward automation and eliminating manual, error-prone data processes

Accepts feedback graciously and creates psychologically safe environments for the team

[NW1]This bullet seems somewhat long/redundant/confusing. Maybe split into 2?

[VS2]Sounds good.