Data Engineer Manager

Data Engineering Manager
About the Role
We are looking for a Data Engineering Manager who can combine strong data engineering expertise with people leadership.
In this role, you will lead and mentor a team of Data Engineers responsible for building scalable solutions for data acquisition, transformation, integration, and analytics. You will provide technical direction, support complex customer data challenges, and work closely with engineering leaders, stakeholders, and cross-functional teams to deliver reliable, high-quality data solutions.
This is a hands-on leadership role for someone who enjoys developing people, solving complex data problems, and improving engineering practices and processes.
What You'll Do
Lead & Develop the Team
Lead, coach, mentor, and develop a team of Data Engineers.
Provide performance feedback and support career development.
Guide team members on technical growth and engineering best practices.
Support onboarding, training, workload planning, and resource allocation.
Build a culture of collaboration, accountability, and continuous learning.
Provide Technical Leadership
Guide the design, development, and maintenance of scalable data solutions.
Review technical designs, data mappings, transformation logic, and implementation approaches.
Provide technical guidance on complex data and customer implementation challenges.
Act as an escalation point for technical and customer-impacting issues.
Ensure solutions meet expectations for data quality, reliability, security, and compliance.
Promote practices around testing, monitoring, documentation, automation, and maintainability.
Collaborate & Manage Stakeholders
Partner with other engineering leaders to align technical standards, delivery approaches, and priorities.
Work with stakeholders to understand requirements, manage risks, and support delivery.
Collaborate with R&D and cross-functional teams to identify improvement opportunities.
Communicate technical concepts and project updates clearly to technical and business stakeholders.
Participate in leadership discussions and help shape team strategy and execution.
Drive Continuous Improvement
Improve engineering processes, documentation, templates, and reusable solutions.
Identify opportunities for automation and operational efficiency.
Establish and monitor operational metrics.
Promote data governance, lineage, and data quality practices.
Contribute to workforce planning, knowledge sharing, and organizational improvement initiatives.
What We're Looking For
5+ years of experience in Data Engineering or related data engineering roles.
1+ year of direct people management experience.
Proven experience leading and mentoring Data Engineers or similar engineering teams.
Strong understanding of data engineering, ETL/ELT, data acquisition, transformation, and integration.
Strong knowledge of modern data platforms and cloud technologies, particularly:
Snowflake
Azure
Databricks
Azure Data Factory
Ability to understand, review, and guide code related to data engineering and ETL solutions.
Strong analytical, troubleshooting, and problem-solving skills.
Experience working with healthcare data and EHR/EMR systems.
Strong communication and presentation skills, with the ability to work with technical teams, business stakeholders, customers, and senior leadership.
Experience working in Agile environments.
Good to Have
Experience with Health Catalyst DOS or Ignite platforms.
Experience with data governance, data lineage, and data quality.
Experience supporting complex enterprise or customer implementations.
Experience driving automation and process improvements across engineering teams.
Bachelor's or Master's degree in Computer Science, Data Engineering, Technology, or a related field.
What Success Looks Like
In this role, you'll help the team:
Build better data solutions
Deliver scalable, reliable, and high-quality data products.
Grow strong engineers
Develop technical capability, ownership, and career growth within the team.
Solve complex problems
Provide technical direction and help resolve challenging data and customer issues.
Improve how we work
Drive automation, standardization, and continuous improvement across Data Engineering.
Information Security & Compliance
Employees are expected to follow organizational requirements related to Information Security, Acceptable Use Policy, HIPAA Privacy and Security, and the protection of company information and systems.

Work arrangement
Hybrid