Lead Data Analyst

Gifthealth is revolutionizing healthcare by simplifying prescription and health service management through a seamless, personalized, and efficient customer experience. The Lead Data Analyst will own analytical direction for a domain, define and validate metrics, manage a small team of analysts, and partner with operations, account teams, data engineering, BI, and leadership to drive data-informed decisions.

Responsibilities:

• Set the analytical direction for a domain: decide the canonical metrics, which sources are authoritative for which question, what gets modeled in dbt versus answered ad hoc, and the validation required before a result goes to a client or an executive
• Drive metric definitions for the domain into the dbt layer, in partnership with data engineering and BI, so that definitions live in models rather than in a Looker filter, a spreadsheet, or an analyst's head, and so any headline number can be traced to where it is computed and what it excludes
• Manage two to three data analysts as direct reports: 1:1s, review of their SQL and conclusions, growth plans, and performance conversations
• Own the sequencing of analysis in the domain, including what the business needs next, what recurring reporting can be retired, and what to say no to, negotiating directly with operations leads, account teams, and the Director
• Take on the hard questions in the domain that require patient-level reconstruction, an identified mechanism in the data, and an owned action, such as an unexplained metric shift or a client asking why two internal numbers disagree
• Keep shared metrics shared across domains by working with other leads and BI, escalating rather than forking a definition when there is disagreement
• Know where a join quietly drops rows across the underlying systems (NDP, LDZ, IDP, BestRx, and the entity-resolution layer that resolves identity across roughly thirty source systems), and teach that to the analysts on the team

Requirements:

• equivalent hands-on experience is fully acceptable
• Typically 7 to 10 years of hands-on data analysis experience, with a track record as the senior analyst others checked their work with
• A track record as the senior analyst others checked their work with on ambiguous business questions that ended in a decision someone acted on
• Deep SQL: comfortable in a warehouse with a few hundred dbt models, able to read other people's SQL critically, and checks for fan-out before trusting a total
• Experience setting metric definitions that other people then had to live with, documented well enough that they held
• Experience managing or leading analysts, or informal experience doing so and wanting the accountability that comes with the title
• Judgment about your own results: a number that looks great or alarming gets validated against a second source before it is shared
• Able to explain a finding to an operations lead, an account manager, and the Director in the same week, and to tell an account team what the data does not support without hedging or overclaiming
• Comfort working in an unfinished stack, with two migrations in flight and the ground moving
• Treats PHI, masking, BAAs, and role-based access as part of the daily workflow by default, not a compliance review at the end
• Strong understanding of healthcare data, PHI, and HIPAA requirements
• Proven ability to lead a small team and drive performance across the domain
• Excellent leadership, communication, and data-driven decision-making skills
• Pharmacy, specialty pharmacy, healthcare, or payer data experience, including claims, adjudication, prior authorization, NDCs, or the prescription lifecycle
• Manufacturer patient-support or hub program experience, especially where the manufacturer receives the reporting directly
• dbt experience to the point of writing and testing models yourself and reviewing a teammate's
• Looker and LookML experience, or experience migrating reporting off a legacy BI tool without freezing the business during the migration
• Python for analysis that SQL is not well suited to
• Experience owning a metric layer or definitions catalog that multiple teams depended on
• A degree is optional
• Formal people-management experience is welcome but not required; we will also consider a strong Senior Data Analyst ready for the step up