Manager, Data Engineering – Analytics

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

📋 Description

• Lead and oversee the Data Engineering & Analytics team, offering mentorship, guidance, and support.

• Manage the team's intake, prioritization, scheduling, and ensure stakeholder transparency through Jira.

• Design, develop, and sustain data products utilizing Python, SQL, dbt, Airflow, BigQuery, and contemporary technologies.

• Advocate for a dbt-first, governed methodology with verified, traceable, and automated models.

• Spearhead the expansion into predictive and prescriptive analytics, including forecasting, recommendation systems, and clustering/segmentation.

• Establish validation, monitoring, and governance protocols for machine-learning models within a healthcare framework.

• Set strategic objectives for the team that align with the company’s data goals.

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

• Track team performance and growth through feedback, code assessments, and training sessions.

• Generate high-quality, testable, maintainable code while establishing coding standards.

• Enhance deployment procedures, sprint planning, monitoring, incident responses, escalation processes, and team workflows.

• Promote the adoption of AI tools such as Cursor and Claude Code.

• Troubleshoot intricate issues within data pipelines and models.

• Manage the data team's contributions to monthly closures and scorecards, ensuring accurate and timely reporting and invoicing.

• Assess and enhance delivery reliability, efficiency, productivity, data quality, reporting timeliness, stakeholder satisfaction, scalability, and system optimization.

• Perform additional duties as assigned or deemed necessary.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Information Systems, or a related field; relevant work experience may be considered as a substitute for a degree.

• Over 5 years of experience in data analytics, data engineering, or a related data field.

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

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

• Proven track record in formulating, communicating, and advocating for strategic direction within a data team.

• Strong skills in leadership, team management, mentoring, and technical team development.

• Capable of leading change management initiatives and influencing stakeholders across various functions.

• Excellent data analysis and presentation abilities.

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

• Extensive knowledge of SQL and data engineering, including ETL/ELT solutions.

• Proficiency in BigQuery, dbt, Airflow, and Python is required.

• Experience managing intake and prioritization processes, such as Jira, ensuring backlog transparency.

• Familiarity with machine learning and data science concepts, including forecasting/time-series methods, recommendation engines, and clustering/segmentation.

• Knowledge of the Python ecosystem for machine learning, including libraries like pandas and scikit-learn.

• Willingness to promote AI-assisted development and analytics tools.

• Experience in handling sensitive data responsibly; familiarity with HIPAA/PHI is strongly preferred.

• Exceptional communication and interpersonal skills.

• Must be at least 18 years old.

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

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

• Must be able to remain at a designated workstation throughout the workday and operate computers and office productivity tools.

• Selected candidates may be required to undergo a background check and/or drug screening.

🏝️ Benefits

• Fully remote work available at approved locations within the United States.

• Flexible remote work arrangements.

• Opportunity to make a meaningful contribution to a mission supporting older adults and their families.

• A mentorship-driven, collaborative, and continuous learning environment.

• Access to training opportunities.

• Regular AI experimentation and sharing as an integral team practice.

• An equal opportunity workplace that values diversity, equity, and inclusion.

• Reasonable accommodations available for qualified individuals with disabilities.