Business Data Analyst

AristaMD•San Diego, CA

1d•$120,000 - $140,000•Remote

About The Position

AristaMD is the premier virtual-first professional medical corporation providing specialty care. We enable risk-bearing PCPs to improve access to specialty care, enhance clinical outcomes, and reduce the total cost of care. Our program, SC360, provides point-of-care referral decision support, routing every referral by clinical appropriateness to one of three tracks: an eConsult, a virtual specialty care visit, or a curated in-person specialty network. This ensures every patient gets the right care, at the right time, through the right channel. We're looking for a highly technical and consultative Business Data Analyst to join our growing analytics team. This person will own analytics platform governance, lead the ongoing migration of our reporting infrastructure to Power BI, and serve as a strategic partner to clinical, operations, and leadership teams across a fast-growing healthcare technology company. This is not a “build the report and move on” role. We're looking for someone who proactively automates repetitive workflows, designs scalable data solutions, and helps teams build the right thing, not just whatever was asked for last. You'll operate inside a mature, enterprise-scale Power BI environment supporting multiple business lines and client-facing reporting programs. You'll join a team that's actively investing in modern analytics infrastructure and AI-assisted workflows, with the autonomy to shape how the organization measures, automates, and scales its reporting practices. This role has a clear growth path from report development into analytics strategy leadership.

Requirements

Minimum of 7 years of relevant work experience in business intelligence, data analytics, or a related field
Expert-level proficiency in Power BI (including DAX); strong working knowledge of Tableau or similar legacy BI tools
Strong SQL across multiple platforms (PostgreSQL and Snowflake) and Python skills
Proven experience designing and managing ETL pipelines in a modern data warehouse environment (e.g., PostgreSQL, Snowflake)
Experience integrating AI models into analytical or coding workflows, and automating routine business processes

Nice To Haves

Healthcare domain knowledge, including familiarity with healthcare billing, claims analysis, medical coding (CPT, ICD-10), and the broader payer landscape (e.g., Medicare, Medicaid, commercial payers)
Experience in healthcare, insurance, or another regulated data environment
Experience with data governance frameworks and PHI/PII compliance considerations
Experience partnering with finance or compensation teams on payment and data reconciliation logic

Responsibilities

Own the migration of legacy reporting tools to Power BI.
Establish and maintain certified, well-documented, and supportable reporting environments that the whole organization can trust.
Act as the primary owner of key reporting assets and dashboards, accountable for their ongoing accuracy, performance, and upkeep.
Lead high-impact data initiatives from discovery through implementation, including compensation and payment data portals, claims and utilization analysis, and enterprise data warehousing work.
Define metric definitions, business rules, UAT processes, and acceptance criteria, and see projects through to production.
Proactively identify repetitive, manual reporting processes and automate them, turning multi-hour manual processes into reliable automated pipelines.
Use AI tools and scripting (e.g., workflow automation platforms, scripting languages) to streamline recurring report distribution and internal data workflows.
Develop standardized, reusable reporting packages and automate their recurring distribution to stakeholders and clients, for both internal and external reports.
Partner directly with business stakeholders across clinical, customer experience, and operations functions.
Translate ambiguous business needs into clear analytical requirements and guide teams toward durable solutions rather than one-off fixes.
Build and maintain documentation including data dictionaries, reporting standards, and workflow diagrams.
Help ensure the integrity and scalability of an enterprise data warehouse as the organization grows.
Monitor data quality and perform validation checks across reporting layers to ensure accuracy and consistency.
Troubleshoot and resolve data integration issues between source systems, ETL pipelines, and the data warehouse.