Manager, Data Engineering & Analytics

Role Overview

As the Manager of Data Engineering & Analytics, you will lead The Helper Bees’ Data Engineering and Analytics team, responsible for both the technical execution and strategic direction of data across the company. Your leadership will be key in ensuring the team produces accurate, governed, and on-time data reports, invoices, and analyses that our internal leaders and external partners depend on.

What You Will Do

You will manage and develop a high-performing team of Data Engineers and Data Analysts, guiding their career growth, performance, and skill development. You will own how the team takes in, prioritizes, and delivers work, and you will set clear, achievable goals that ladder to the company’s data objectives.

Why It Might Be a Fit

You will work closely with leaders from Product, Accounts, Operations, and the C-suite — as well as external clients and partners — to ensure alignment and successful delivery of the data strategy, acting as both a leader and an advocate for the data function across the organization.

Requirements

• 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 with Tableau, Salesforce data, and Azure/Synapse a plus (PostgreSQL, PowerBI nice-to-have).
• 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). Hands-on ML experience and exposure to deploying/monitoring models in production strongly preferred.
• Familiarity with, or willingness to drive, AI-assisted development and analytics tooling.
• Experience managing or transitioning work from external consultants/vendors a plus.
• 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.

Benefits

• Flexible remote work options
• Reasonable accommodations to qualified individuals with disabilities during the job application and interview process
• Background check and/or drug screen as part of the standard hiring process
• Compliance with applicable federal, state, and local laws regarding these screenings