• Lead large, complex ad-hoc and planned analytical initiatives from problem definition through insight delivery. • Identify analytical opportunities, proactively surface business questions, and recommend data-driven courses of action. • Apply advanced analytical and statistical techniques to evaluate trends, performance drivers, customer behavior, and business outcomes. • Translate complex analyses into clear, compelling insights and recommendations for senior leaders. • Act as a strategic partner and liaison between analytics, technology, and business teams. • Collaborate with stakeholders across functions to define requirements, align on objectives, and influence decision-making. • Coordinate and prioritize multiple analytical projects simultaneously, ensuring quality, accuracy, and timeliness. • Leverage advanced querying, database, and analytical tools to extract, analyze, and validate large, complex datasets. • Present analytical findings and recommendations to a broad audience, including senior management.

• Analyze business challenges and provide business analytics for decision-making. • Translate complex requirements into scalable data transformations using Snowflake. • Present findings to stakeholders at multiple levels. • Build complex data structures and reporting processes to measure business performance. • Design efficient workflows for data transformation and analysis. • Propose and implement best practices in data integrity and validation.

• Lead implementation initiatives, supporting design, build, testing, and deployment of FHIR‑based data solutions • Map healthcare data domains (Member, Eligibility, Coverage, Claims, Prior Authorization, Clinical) to FHIR resources • Apply IGs (US Core, Da Vinci, CARIN), and collaborate on FHIR API design and validation • Build mappings, resource definitions, extensions, and value sets • Work with architects on payloads, search parameters, and versioning • Use validators, test servers, and reference implementations • Support normalization, transformation, and reconciliation across systems • Participate in unit/integration/UAT, produce mappings, specs, and test scenarios

• Gather and document requirements from internal stakeholders • Define, track, and report on key performance indicators (KPIs) • Translate business questions into data models, queries, and dashboards • Prepare clear reports and present findings to technical and non-technical audiences • Help build and maintain ELT pipelines from Segment into Snowflake • Monitor and validate event data flowing through Segment — checking completeness, consistency, and correct destination mapping • Assist with data quality audits across the Segment → Snowflake → Looker stack • Investigate and document data anomalies and pipeline failures • Support data model development and maintenance in Snowflake • Build dashboards and reports in Looker • Write and optimize SQL queries against Snowflake • Assist with basic LookML development: views, explores, and measures • Apply data visualization best practices for clarity and audience fit • Use AI assistants (Claude, Copilot, ChatGPT) to speed up SQL writing, documentation, and analysis • Apply text-to-SQL and LLM-based tools for faster data exploration • Prototype basic AI features: anomaly detection and automated report summarization • Contribute ideas for AI and automation adoption within the team • Track tasks and participate in Agile sprints using Jira • Use Git/GitHub for version control of SQL, LookML, and Python scripts • Participate in code and dashboard reviews • Document data models, event schemas, metric definitions, and pipeline logic