BI Analytics Lead

At our company, we move fast, adapt quickly, and turn challenges into opportunities—all while keeping quality at the heart of everything we do. We believe that work should be a positive and respectful place, and that with the right mindset, anything is achievable.

Fulfill the essential promise of pharmacy care and help people to live to their healthiest, happiest, and fullest potential.

To be the disruptive force that drives meaningful change within pharmacy services.

This position is not eligible for employment visa sponsorship. Applicants requiring sponsorship now or in the future, including those on STEM OPT, are not eligible for consideration.

We are actively looking for a passionate Lead of BI Analytics to join our team and help inform the direction of Health Dyne Business through data, s role serves as both a hands-on analytics leader and a player-coach, responsible for developing reporting solutions, identifying KPIs that drive the business, performing analysis to support strategic and tactical initiatives, and translating findings into clear insights for less-technical audiences.

The Lead will also coach, mentor, and develop BI analysts by providing guidance on analytical approach, technical execution, stakeholder communication, prioritization, and quality standards. Successful candidates will be comfortable creating and optimizing table structures, generating reports consumed across the Business organization, partnering with cross-functional stakeholders, and helping establish scalable best practices for analytics delivery. Strong SQL experience is required; scripting skills and a background in operations are highly valuable.

This is a highly visible role that partners with business, product management, operations, and technical teams.

• Develop, coach, mentor, and cross-train BI team members to strengthen analytical capabilities, technical skills, and business acumen.
• Serve as a player-coach by balancing hands-on analytics work with team leadership, prioritization, and delivery oversight.
• Establish and reinforce standards for reporting accuracy, documentation, data governance, quality control, and repeatable analytics processes.
• Partner with team members to assess workload, remove obstacles, assign priorities, and ensure timely delivery of reporting and analytics commitments.
• Design, implement, and support a platform providing ad hoc access to large datasets.
• Manipulate/mine data from database tables (ex. Redshift, MySQL, Oracle, SQL Server) using SQL and ETL.
• Manipulate/mine data from log files, spreadsheets by writing scripts (ex. PERL, Python, UNIX).
• Develop analytical tools: deep-dive tools, UIs, metrics, and dashboard.
• Perform deep-dives and root cause analysis to answer business questions.
• Work with cross-functional stakeholders in defining the source of truth and obsessively making sure the data fidelity is high.
• Effectively communicate (written and verbal) solutions and methodologies to senior leadership.
• Work with engineering teams to enable the appropriate capture and storage of data.
• Complete ad hoc data retrieval and analysis.
• Monitor existing metrics, develop and propose new metrics, and identify new, actionable risk signals.

• 5+ years of progressive experience in business intelligence, data analytics, data engineering, reporting, or related roles, including hands-on experience analyzing and interpreting data from relational databases, cloud data warehouses, or large-scale datasets such as Redshift, Oracle, SQL Server, MySQL, Snowflake, or similar platforms.
• Demonstrated experience building, maintaining, and governing business intelligence solutions using Power BI, Tableau, Quick Sight, or similar visualization tools, with the ability to translate business requirements into scalable dashboards, reports, and executive-ready insights.
• Experience with data modeling, data warehousing, ETL/ELT pipelines, metric definition, and source-of-truth design, including partnering with technical teams to improve data quality, structure, accessibility, and reliability.
• Working knowledge of statistical analysis, forecasting, root cause analysis, and advanced analytics methods; experience with tools such as Python, R, SAS, or similar platforms is preferred.
• Advanced SQL skills required, with practical scripting experience in Python, R, or similar languages to automate workflows, transform datasets, support modeling, and improve repeatable…