Senior Manager of Data Engineer

Accountabilities

• • Lead, mentor, and develop a multidisciplinary team of data engineers and data scientists, fostering collaboration, technical excellence, and continuous improvement.
  • Oversee the design, deployment, maintenance, and scalability of data pipelines, data architecture, and data science models.
  • Ensure the consistent delivery of accurate, reliable, timely, and high-quality data across business and product use cases.
  • Partner with Analytics teams to develop data models and infrastructure that enable scalable and impactful reporting and business insights through Looker.
  • Consult with Product and Engineering teams on upstream data changes, assessing how new features and systems may affect downstream data models, pipelines, and analytics.
  • Define and evolve the organization's data warehousing strategy using Snowflake to support analytics, data science, and product requirements.
  • Establish and enforce data quality standards, governance practices, automated testing, observability, and security controls.
  • Ensure data practices align with relevant compliance requirements, including healthcare data privacy and security standards.
  • Act as the primary liaison between the data function and business stakeholders, gathering requirements, prioritizing initiatives, communicating progress, and maintaining alignment.
  • Develop and execute a strategic roadmap for data engineering and data science that supports broader organizational objectives.
  • Identify and evaluate new data sources, technologies, and data science opportunities that can generate additional business value.
  • Oversee the integration of new data sources into the broader data ecosystem while maintaining reliability and scalability.
  • Remain hands-on by contributing to data engineering and data science codebases, particularly on high-impact initiatives and complex technical challenges.
  • Evaluate modern AI workflows and coding assistants that can improve engineering productivity, pipeline development, scripting, and code generation.
  • Partner across functions to identify opportunities for process improvement, better decision-making, and increased use of data throughout the organization.

  Requirements

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical discipline.
  • 5+ years of experience in data engineering, data science, data architecture, or a closely related field, including at least 2 years in a leadership or management capacity.
  • Experience working in healthcare, insurance, or another highly regulated data environment is strongly preferred.
  • Strong experience with modern data integration technologies, ETL/ELT frameworks, and cloud data platforms.
  • Experience with AWS, Snowflake, and Matillion or dbt is a plus.
  • 3+ years of experience using business intelligence and data visualization tools such as Looker.
  • Experience managing or closely collaborating with Data Science teams, with a practical understanding of machine learning models and statistical analysis.
  • Deep understanding of data pipeline architecture, dimensional data modeling, ELT best practices, and scalable data infrastructure.
  • Strong proficiency in SQL and Python.
  • Experience implementing data quality programs, automated testing frameworks, and continuous observability practices.
  • Familiarity with data governance, zero-trust security principles, and compliance standards.
  • Experience working with healthcare data, HIPAA, or protected health information (PHI) is strongly preferred.
  • Familiarity with modern AI-assisted development workflows and coding tools.
  • Strong communication and stakeholder-management skills, with the ability to explain technical concepts clearly to non-technical audiences.
  • Demonstrated ability to set priorities, build alignment, manage ambiguity, and translate business requirements into effective technical solutions.
  • Hands-on technical mindset with the ability to balance strategic leadership and direct contribution to engineering and data science work.

  Benefits

  • Annual salary range of $162,000–$180,000 USD, with starting compensation determined based on factors such as skills and professional experience.
  • 401(k) retirement plan with employer match.
  • Flexible paid time off.
  • Paid holidays and paid service days.
  • Four-week paid sabbatical.
  • 12 weeks of paid parental leave.
  • Health benefits beginning on the first day of employment.
  • Fully remote work environment.
  • Periodic in-person team retreats.
  • Opportunity to work on technology and data initiatives with meaningful real-world impact in healthcare.
  • Opportunity to lead and develop a multidisciplinary data engineering and data science team.
  • Exposure to modern cloud data platforms, AI-assisted development, analytics, and data science technologies.
  • Collaborative environment focused on continuous learning, innovation, inclusion, and professional growth.
  • Opportunity to contribute to initiatives designed to improve access to evidence-based care and outcomes for children, young adults, and families.