Note: The job is a remote job and is open to candidates in USA. The Helper Bees is a healthcare company focused on helping older adults find and access quality, affordable in-home care. The Manager of Data Engineering & Analytics will lead the data engineering and analytics team, oversee data products and delivery processes, and advance the organization’s predictive, prescriptive, and AI-enabled analytics capabilities. The role also involves people leadership, stakeholder collaboration, data governance, and responsible handling of protected health information.
Responsibilities
- Lead and manage the Data Engineering & Analytics team, providing mentorship, guidance, and support to ensure technical and professional development across a team of mixed tenure, including members still onboarding
- Design, implement, and maintain The Helper Bees' data products using Python, SQL, dbt, Airflow, BigQuery, and other modern technologies
- Own the team's intake and prioritization — how requests come in, get triaged, and get scheduled (managed in Jira) — and make that process legible to stakeholders so they can see where their requests stand and why
- Champion a dbt-first, governed approach: move reporting off manual and bespoke SQL into tested, traceable, automated models, and hold the team to a high reliability bar (on-time delivery and zero manual edits to production data)
- Lead the team's expansion into predictive and prescriptive analytics — guiding the development of ML models for forecasting, recommendation engines, and clustering/segmentation to profile members by diagnosis and need — and put the practices in place (validation, monitoring, governance) to deploy and maintain these models responsibly in a healthcare context
- Set strategic goals for the team, ensuring alignment with the company's data objectives and promoting continuous improvement
- Collaborate with department teams to design, build, test, and implement new features and enhancements that meet internal and external stakeholder needs
- Monitor team performance and development, fostering an environment of growth through regular feedback, code reviews, and training opportunities
- Produce quality, testable, and maintainable code, while setting high coding standards for the team
- Assist in refining and improving development processes such as deployment, sprint planning, monitoring, incident response, escalation, and team workflows
- Drive adoption of AI tooling (e.g., Cursor, Claude Code) as a multiplier for the team's engineering and analytics work — modeling personal use, and making AI experimentation and sharing a standing team practice
- Facilitate problem-solving and innovation within the team, encouraging creative solutions to complex technical challenges
- Act as a technical leader for the team, growing other engineers and analysts through mentorship and example, while ensuring high-quality, scalable, and optimized data systems
- Quickly isolate and debug complex issues across data pipelines and models, helping the team troubleshoot problems effectively
- Collaborate with stakeholders, product teams, operations, external clients, and partners to understand requirements, discuss tradeoffs, and deliver viable solutions
- Own the data team's contribution to the monthly close and scorecard — client and partner reports and invoices delivered accurately and on time — and surface exceptions proactively
- Drive process improvements within the team, measuring the impact on delivery reliability, efficiency, and overall productivity
- Other duties as assigned or necessary to support team and company success
Skills
- Proven experience in crafting, communicating, and promoting strategic direction for a data team
- Strong leadership and team management skills, with experience in mentoring and developing a high-performing technical team, including people still early in their careers
- Ability to lead change management initiatives and influence key stakeholders across functions
- Strong data analysis and presentation skills, with experience in building and improving data warehouses and modern data pipelines
- Extensive experience with SQL and data engineering, including ETL/ELT solutions, and hands-on expertise with modern tooling — BigQuery, dbt, Airflow, and Python required
- Experience owning an intake and prioritization process (e.g., in Jira) and making a backlog transparent to stakeholders
- Working knowledge of machine learning and data science sufficient to set direction and review approaches — including forecasting/time-series methods, recommendation engines, and clustering/segmentation — and the Python ecosystem used to build them (e.g., pandas, scikit-learn)
- Familiarity with, or willingness to drive, AI-assisted development and analytics tooling
- Experience handling sensitive data responsibly; familiarity with HIPAA / PHI handling is strongly preferred given our healthcare context
- Excellent communication and interpersonal skills, with a passion for guiding others and working directly with non-technical and external stakeholders
- Must be 18 years of age or older
- Bachelor's degree in Computer Science, Engineering, Mathematics, Information Systems, or a related field
- Relevant work experience may be considered in lieu of a degree
- 5+ years of experience in data analytics, data engineering, or a related data discipline, with increasing scope and responsibility
- 2+ years of hands-on experience as a Data Engineer or in a highly technical data role (SQL, dbt, and pipeline orchestration such as Airflow)
- 2+ years of direct people-leadership experience, including hiring, coaching, performance management, and driving team execution
- Demonstrated experience leading complex data initiatives from strategy through delivery, including migrations or platform transitions
- Ability to remain at your designated workstation for the duration of the workday
- Constantly operates a computer and other office productivity machinery, such as a phone and Voice over Internet Protocol (VoIP)
- The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations
- The ability to observe details at close range (typically on a computer screen)
- This position offers the flexibility of remote work at approved locations within the United States. Candidates must have a reliable internet connection and a designated work environment conducive to professional phone calls and sensitive data
- Hands-on ML experience and exposure to deploying/monitoring models in production strongly preferred
- Familiarity with HIPAA / PHI handling is strongly preferred given our healthcare context
- Experience delivering — or leading a team to deliver — predictive/prescriptive analytics or machine-learning models (e.g., forecasting, recommendation, or clustering/segmentation) preferred
- Experience with Tableau, Salesforce data, and Azure/Synapse a plus
- PostgreSQL, PowerBI nice-to-have
- Experience managing or transitioning work from external consultants/vendors a plus
Benefits
- This position offers the flexibility of remote work at approved locations within the United States.
Company Overview