Manager, Data Engineering, Analytics

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead and oversee The Helper Bees' Data Engineering & Analytics team.

• Report directly to the Vice President of Business Intelligence.

• Manage and nurture the development of Data Engineers and Data Analysts/Business Analysts.

• Establish the strategic direction, goals, intake, prioritization, and delivery processes for the team.

• Design, implement, and maintain data products utilizing Python, SQL, dbt, Airflow, BigQuery, and other modern technologies.

• Transition reporting from manual and bespoke SQL to automated, tested, and traceable dbt models.

• Ensure the delivery of reliable, accurate, governed, and timely data reports, invoices, and analyses.

• Lead initiatives in predictive and prescriptive analytics, including forecasting, recommendation engines, and clustering/segmentation.

• Establish practices for validation, monitoring, and governance of healthcare machine-learning models.

• Collaborate with Product, Accounts, Operations, C-suite leaders, external clients, and partners.

• Monitor team performance through feedback, code reviews, and training efforts.

• Set and uphold standards for coding, quality, scalability, and maintainability.

• Enhance processes for deployment, sprint planning, monitoring, incident response, escalation, and workflow management.

• Promote the adoption of AI-assisted development and analytics tools such as Cursor and Claude Code.

• Troubleshoot complex issues within data pipelines and models.

• Oversee the data team's contributions to monthly close and scorecard processes, including client and partner reports and invoices.

• Proactively identify exceptions and assess improvements in reliability, efficiency, and productivity.

• Supervise data quality, reporting timeliness, technical leadership, code quality, innovation, stakeholder satisfaction, scalability, and optimization.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, Information Systems, or a related field; relevant work experience may be accepted in lieu of a degree.

• 5+ years of experience in data analytics, data engineering, or a related field, with progressively increasing responsibilities.

• 2+ years of hands-on experience as a Data Engineer or in a highly technical data role.

• 2+ years of direct leadership experience, encompassing hiring, coaching, performance management, and driving team execution.

• Demonstrated ability to craft, communicate, and advocate for the strategic direction of a data team.

• Strong skills in leadership, team management, change management, stakeholder influence, data analysis, and presentation.

• Experience in building and enhancing data warehouses and modern data pipelines.

• Proficient in SQL and data engineering, including ETL/ELT solutions.

• Required experience with BigQuery, dbt, Airflow, and Python.

• Familiarity with Tableau, Salesforce data, and Azure/Synapse is a plus; knowledge of PostgreSQL and Power BI is desirable.

• Experience managing an intake and prioritization process, such as Jira.

• Working knowledge of machine learning and data science, including forecasting/time-series methods, recommendation engines, and clustering/segmentation.

• Experience with the Python ecosystem, including pandas and scikit-learn.

• Hands-on experience in machine learning and production model deployment/monitoring is strongly preferred.

• Familiarity with or a willingness to drive AI-assisted development and analytics tools.

• Experience in managing or transitioning work from external consultants/vendors is a plus.

• Proven ability to handle sensitive data responsibly; familiarity with HIPAA/PHI is strongly preferred.

• Excellent communication and interpersonal skills are essential.

• Candidates must be 18 years of age or older.

• Demonstrated experience leading complex data initiatives from strategy through delivery, including migrations or platform transitions.

• Experience in predictive/prescriptive analytics or machine-learning model delivery is preferred.

• Reliable internet connection and a designated work environment conducive to professional phone calls and handling sensitive data.

• Ability to remain at a designated workstation for the entire workday.

• Proficiency in operating a computer and office productivity machinery.

• Capability to communicate and exchange accurate information effectively.

• Ability to observe details at close range.

🏝️ Benefits

• Remote work at approved locations within the United States.

• Flexible remote work arrangements.

• Opportunities for mentorship, collaboration, and continuous learning.

• Career growth, performance feedback, code reviews, and training opportunities.

• Equal opportunity workplace.

• Reasonable accommodations provided during the application and interview process.

• Potential background check and/or drug screening as part of the hiring process.