• Architect and build the core Growth Analytics data environment with Snowflake as the central platform • Design, implement, and maintain scalable data pipelines, integrations, and transformation workflows across internal business, product, operational, sales, marketing, finance, and planning systems • Build trusted, reusable data models and curated datasets to support internal analytics, reporting, forecasting, growth planning, and Strategy & Operations workflows • Develop and manage BI environments in Power BI and Looker, including semantic models, governed datasets, dashboard foundations, access patterns, and performance standards • Build AI-ready data layers to support internal intelligence solutions, including structured datasets, metadata, documentation, business definitions, and governed access patterns • Establish standards for data quality, testing, observability, lineage, documentation, naming conventions, metric definitions, and production reliability • Partner with internal stakeholders to translate business questions into scalable data products, reporting layers, and analytics-ready infrastructure • Create and maintain clear documentation for source systems, pipelines, data models, metric definitions, BI assets, and AI-ready datasets • Lead technical design discussions, make architecture recommendations, and mentor analytics, BI, and data partners on scalable data practices • Help move AOS from fragmented reporting and manual data processes toward a reliable, governed, and scalable intelligence layer

Role Description As a PostgreSQL Infrastructure DBA, you will: - Install, configure, upgrade and maintain PostgreSQL databases in production and non-production environments. - Manage database availability, high availability configurations, and failover processes. - Leverage enterprise-approved AI tools to enhance productivity and innovation by streamlining workflows and automating repetitive tasks. - Evaluate emerging trends to drive continuous improvement and strategic innovation. - Monitor database health and performance; proactively identify and resolve performance bottlenecks. - Perform query and system-level performance tuning. - Perform regular recovery testing and execute disaster recovery procedures as required. - Ensure data integrity and recoverability at all times. - Monitor database security and prevent unauthorized access. - Manage user access, roles, and permissions in alignment with security standards and compliance requirements. - Schedule and execute routine database maintenance activities. - Troubleshoot and resolve production database issues, including data-related incidents. - Provide best-practice guidance to development and application teams on database usage. - Develop and enhance automation to streamline database operations and data loading processes. - Utilize PostgreSQL utilities and tools and monitoring/management solutions to maintain the environment. - Manage user access and permissions by adding and removing users as required. - Maintain the database using different utilities, including using pg_ctl and psql. Qualifications - High School Diploma/GED. - 3+ years of experience as a PostgreSQL Infrastructure DBA supporting Postgres in a large-scale enterprise environment, including managing databases of 10+ TB. - 2+ years of experience working with public cloud environment. Requirements - Healthcare experience. - Experience with MySQL or additional relational database platforms. - Working knowledge of implementing AI-driven tools used in database operations, monitoring, and support environments. Benefits - Comprehensive benefits package. - Incentive and recognition programs. - Equity stock purchase. - 401k contribution (all benefits are subject to eligibility requirements).

• Designing and developing modern, data-centric applications that support clinical and operational workflows • Building scalable data pipelines, transformation and enrichment processes, and intuitive user interfaces • Mentoring junior Data Engineers

• Assist in the design and development of ETL/ELT workflows using Databricks to move and transform data efficiently. • Maintain and enhance existing Python and SQL codebases, ensuring data integrity and pipeline reliability. • Debug and resolve defects in data processing pipelines under the guidance of senior team members. • Clearly document code changes, data models, and technical processes to ensure team transparency. • Work closely with other data engineers and product teams to translate basic business needs into technical solutions.