Data Engineering Manager

Health Catalyst; Hyderabad; On-site; INR 2,800,000 - 5,200,000; Full time

Job summary

Health Catalyst is seeking a Data Engineer Manager to lead a team focused on data acquisition, transformation, and integration for enterprise solutions. The role combines technical leadership with people management to deliver scalable, reliable data solutions in a healthcare context.

You will mentor engineers, drive best practices, ensure data quality and security, and collaborate with stakeholders to align priorities with organizational goals.

Qualifications

• 5+ years of experience in data engineering or related roles.
• 1+ years of direct people management experience.
• Experience leading and mentoring Data Engineers or closely related teams.
• Strong knowledge of data platforms and cloud technologies such as Snowflake, Azure, Databricks, and Azure Data Factory.
• Familiarity with Agile development methodologies.
• Experience with healthcare data and EHR/EMR systems is preferred.

Responsibilities

• Lead, coach, mentor, and develop a team of Data Engineers.
• Provide regular performance feedback, career development guidance, and technical mentorship.
• Foster a culture of accountability, collaboration, continuous learning, and operational excellence.
• Support onboarding and training of new team members.
• Contribute to development and adoption of best practices, standards, and reusable assets across Data Engineering teams.
• Ensure workload balancing and resource planning across projects.
• Partner with other Data Engineering leads to align delivery approaches and standards.
• Contribute to organizational planning and workforce development initiatives.
• Collaborate with peer leaders to balance resources and share best practices.
• Participate in leadership forums to shape team strategy and execution.

Skills

Data engineering

People management

Leadership

ETL concepts

Data governance

Education

Bachelor’s or Master’s degree in technology/CS

Tools

Snowflake

Azure

Databricks

Azure Data Factory

Job description

The Data Engineer, Manager is responsible for leading a team of Data Engineers focused on acquiring, transforming, and managing data that powers enterprise solutions. This role combines technical expertise with people leadership to ensure the delivery of scalable, reliable, and innovative data solutions. The ideal candidate will have experience managing Data Engineering teams, providing technical guidance, and collaborating with stakeholders to align priorities with organizational goals.

• Lead, coach, mentor, and develop a team of Data Engineers.
• Provide regular performance feedback, career development guidance, and technical mentorship.
• Foster a culture of accountability, collaboration, continuous learning, and operational excellence.
• Support onboarding and training of new team members.
• Contribute to the development and adoption of shared best practices, standards, and reusable assets across Data Engineering teams.
• Ensure appropriate workload balancing and resource planning across projects and operational support activities.
• Partner with other Data Engineering team leads to align delivery approaches, technical standards, and operational priorities.
• Contribute to organizational planning, workforce development, and continuous improvement initiatives.
• Collaborate with peer leaders to balance resources, address delivery risks, and share best practices.
• Participate in leadership forums to help shape team strategy, processes, and execution models.
• Support enterprise objectives through cross-team coordination and knowledge sharing.

Technical Leadership

• Lead the design, development, implementation, and maintenance of scalable data acquisition, transformation, and integration solutions.
• Provide technical guidance on complex customer implementations and data challenges.
• Serve as an escalation point for technical issues and customer-impacting concerns.
• Review technical designs, data mappings, transformation logic, and implementation approaches.
• Ensure data quality, integrity, security, and compliance across delivered solutions.
• Drive adoption of engineering best practices including testing, documentation, monitoring, and automation.

Operational Excellence & Continuous Improvement

• Partner with other team leads to develop and improve processes, documentation, templates, and tools that increase consistency, efficiency, and quality.
• Partner with R&D teams to identify enhancement opportunities and influence platform direction.
• Establish operational metrics and monitor team performance.
• Drive automation initiatives that reduce manual effort and improve delivery consistency.
• Promote adoption of data governance, lineage, and quality management practices.

What You Bring to the Role

• Deep understanding of data engineering principles, ETL concepts, and best practices.
• 5+ years of experience in Data Engineering or related data engineering roles.
• 1+ years of direct people management experience, including coaching, performance management, and career development.
• Experience leading and mentoring Data Engineers or closely related engineering teams.
• Strong knowledge of data platforms and cloud technologies such as Snowflake, Azure, Databricks, and Azure Data Factory.
• Ability to understand and review code related to ETL, data acquisition, and data transformation.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Experience with healthcare data and EHR/EMR systems is preferred.
• Strong communication and presentation skills, with the ability to engage technical teams, business stakeholders, and senior leadership.
• Familiarity with Agile development methodologies.

Preferred Experience & Education

• Bachelor's or Master's degree in technology, data engineering, computer science, or a related field.
• Experience with data governance, data lineage, and data quality practices is a plus.
• Experience supporting complex customer implementations or enterprise data solutions is a plus.

Information Security & Compliance Responsibilities

• Maintain compliance with training directives required by the organization pertaining to Information Security, Acceptable Use Policy, and HIPAA Privacy and Security.
• Adhere to and comply with the organization's Acceptable Use Policy.
• Safeguard information system assets by identifying and reporting potential and actual security events to the appropriate Security and Compliance Officers.