Manager Data Analytics and Engineering

About this role

Capital Health is the region's leader in providing progressive, quality patient care with significant investments in our exceptional physicians, nurses and staff, as well as advanced technology. Capital Health is a dynamic health care resource accredited by the DNV that includes two hospitals, an outpatient center, satellite ED, and an expansive network of primary and specialty care. Capital Health Medical Group is made up of more than 600 physicians and other providers who offer primary and specialty care, as well as hospital-based services, to patients throughout the region.

Capital Health recognizes that attracting the best talent is key to our strategy and success as an organization. As a result, we aim for flexibility in structuring competitive compensation offers to ensure we can attract the best candidates.

The listed pay range or pay rate reflects compensation for a  full-time equivalent (1.0 FTE)  position. Actual compensation may differ depending on assigned hours and position status (e.g., part-time).

Pay Range: $124,217.60 - $162,302.40 Scheduled Weekly Hours: 40 Position Overview SUMMARY (Basic Purpose of the Job) The Manager of Data Analytics & Engineering is responsible for leading the design, development, and operational support of Capital Health’s enterprise data platforms and data pipelines. This role ensures that data engineering capabilities align with organizational strategy, IT operations, and enterprise architecture standards. The Manager provides leadership to the data analytics and engineering team, drives operational excellence, and partners with business and clinical stakeholders to deliver reliable, scalable, and secure data solutions.

MINIMUM REQUIREMENTS: Education: Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field required. Additional years of experience may be considered in lieu of a formal degree. Experience: Five years of progressively responsible experience in data engineering or related technical disciplines, including two years of leadership or people management experience if accompanied by a Bachelor's degree. Eight years of progressively responsible experience in data engineering, or related technical field including two years of leadership or people management experience if accompanied by a high school diploma or equivalent. Experience working in enterprise IT environments required. Knowledge and Skills: Strong leadership and operational management capabilities. Ability to align data initiatives with organizational and IT strategy. Excellent communication and cross functional collaboration skills. Focus on reliability, scalability, and performance. Strategic thinker with strong execution and follow through. Strong SQL and Python skills required. Experience with modern data platforms (Snowflake, Databricks, Redshift, BigQuery). Experience with ETL/ELT tools (dbt, Airflow, Informatica, Talend, etc.). Cloud platform experience (Azure, AWS, or GCP). Distributed data processing experience (Spark). Data modeling expertise (dimensional and normalized). Familiarity with CI/CD, DevOps, and infrastructure as code practices. Special Training: Preferred: Experience working within IT Operations or Infrastructure organizations. Familiarity with ITSM frameworks (e.g., ITIL). Experience with monitoring/observability tools. Exposure to real time/streaming technologies (Kafka, Kinesis). Cloud certifications (Azure, AWS, or GCP) preferred.

ESSENTIAL FUNCTIONS: • Lead, mentor, and develop a team of data engineers. Establish team goals aligned with IT Operations and enterprise priorities. Foster a culture of reliability, accountability, and continuous improvement. Oversee hiring, workforce planning, and performance management.

• Design and maintain scalable enterprise data platforms (data warehouse, data lake, lakehouse). Ensure alignment with enterprise IT architecture, standards, and governance.

• Partner with infrastructure and cloud teams to optimize performance, cost, and resiliency. Ensure high availability, disaster recovery readiness, and operational stability.

• Oversee development and maintenance of ETL/ELT pipelines. Ensure data pipelines meet SLAs for performance, quality, and uptime.

• Implement monitoring, alerting, and incident response processes. Drive automation, standardization, and operational efficiency.

• Collaborate with IT Operations on deployment, monitoring, and support of data platforms. Ensure data systems integrate effectively into enterprise support models.

• Contribute to ITSM processes including incident, problem, and change management. Support audit, compliance, and risk management initiatives.

• Partner with BI, analytics, clinical, and business teams to deliver data solutions. Translate business needs into scalable technical designs.

• Works closely with security, governance, and enterprise architecture teams. Implement and enforce data quality standards, monitoring, and stewardship practices.

• Ensure compliance with data privacy, regulatory, and security requirements.

• Evaluate and implement modern data technologies and tools. Stays current with industry trends and recommends improvements to platforms and processes.

• Contributes to long term data strategy and modernization initiatives.

• Perform other duties as assigned.

PHYSICAL DEMANDS AND WORK ENVIRONMENT:

• Frequent physical demands include: Sitting , Wrist position deviation , Keyboard use/repetitive motion

• Occasional physical demands include: Standing , Walking , Climbing (e.g., stairs or ladders) , Carry objects , Push/Pull , Twisting , Bending , Reaching forward , Reaching overhead , Squat/kneel/crawl , Pinching/fine motor activities

• Continuous physical demands include: Talk or Hear

• Lifting Floor to Waist 15 lbs. Lifting Waist Level and Above 10 lbs.

• Sensory Requirements include: Accurate Near Vision, Accurate Far Vision, Color Discrimination, Minimal Depth Perception, Minimal Hearing

• Anticipated Occu

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