Role Description Protera Health is seeking an experienced Data Analyst to lead and support data operations, reporting, analytics, and customer data management across the organization. This highly visible, cross-functional role will closely collaborate with leadership, operations, product, engineering, and customers. The ideal candidate is passionate about solving complex problems, working with healthcare data, developing reporting infrastructure, and empowering organizations to make better decisions through data. This is a unique opportunity for someone who wants broad ownership in building the data foundation of a rapidly growing healthcare company. Key Responsibilities - Manage customer data implementations and ongoing data operations - Process, validate, and reconcile eligibility, claims, enrollment, and member roster files - Develop and maintain dashboards, reports, and operational metrics - Create engaging, customer-facing reporting and analytics - Analyze healthcare claims, utilization, engagement, and outcomes data - Support data movement across Salesforce, Healthie, reporting systems, and customer platforms - Identify opportunities for automation and process improvement - Participate in customer meetings related to data, reporting, and implementations - Partner with operations, product, and engineering teams to solve business problems using data - Document workflows, reporting logic, and data processes Qualifications - 3+ years of experience in data analytics, healthcare analytics, business intelligence, or related fields - Experience with healthcare claims data - Strong SQL skills - Proficiency with dashboarding and reporting tools - Analytical problem-solving abilities and keen attention to detail - Excellent communication and organizational skills - Ability to work independently in a fast-paced environment - Skill in explaining technical concepts to non-technical audiences Preferred Qualifications - Experience with Salesforce data and reporting - Experience with healthcare eligibility and enrollment data - Background in healthcare, digital health, health plans, or value-based care - Experience with data warehousing and ETL processes - Startup experience - Familiarity with predictive analytics or statistical modeling Benefits - Fully remote (United States) - Competitive compensation based on experience - Bonus opportunity - Equity opportunity - Healthcare benefits - PTO - 401(k)

• Translate broad questions into well-defined analytic approaches, including defining populations, time windows, comparison groups, and appropriate methodologies; • Provide ad-hoc analyses to drive insights, provide overviews of major conclusions, constraints or cautions; • Serve as a technical liaison and subject matter expert for complex analytic questions; • Recommend best courses of action based on analytic findings, tradeoffs, and business constraints; • Apply working knowledge across multiple disciplines (analytics, statistics, data engineering, business context) to create innovative solutions; • Collaborate with researchers, data scientists, reporting, and business stakeholders to define goals, success metrics, and analytic approaches; • Leverage DBT, SQL, Python and GitHub to extract, transform, and analyze large complex datasets; • Provide support for products and applications powered through dashboard and reporting services; • Process confidential data and information according to guidelines.

Title: 14391 - Data & Analytics Lead | Houston, TX (Remote) Location: Houston, TX, US Full time Remote KellyOCG is partnering with a Fortune 50 energy client on a large-scale enterprise transformation program. We are seeking a Sr Business Analyst with deep data and analytics expertise to serve as the project-based Data & Analytics Lead. In this role you will partner with the client’s analytics leadership to evaluate, plan, and implement how dashboards and reporting evolve through a multi-year transition. Our Sr Business Analyst – Data & Analytics is accountable for: - Reviewing current dashboards, reporting logic, data sources, and dependencies to define requirements that support the transition state - Partnering with the client’s Data & Analytics Lead to co-develop how dashboards and reporting should evolve through transition into steady state - Providing technical feasibility input, dependency mapping, risk identification, and execution approach during transition planning - Conducting impact assessments on existing dashboards and reporting related to platform changes, data model modifications, and taxonomy updates - Executing dashboard enhancements beyond base scope: updating reporting logic, calculations, structures, and designs to support evolving needs - Identifying gaps between current-state dashboards, platform-delivered reporting, and business needs — then developing and implementing solutions - Ensuring dashboards are tested, validated, accurate, and structured to maintain stability during transition without disrupting business continuity - Preparing comprehensive handoff documentation including technical specifications, data source mappings, calculation logic, known dependencies, and recommended maintenance procedures Essential Skills, Knowledge & Experiences: - 5+ years of experience in data analytics, business intelligence, or reporting within enterprise environments - Hands-on experience designing, building, and enhancing dashboards and reports in Power BI, Tableau, or similar tools - Strong SQL skills for data querying, validation, and analysis - Strong analytical skills with the ability to assess data models, reporting logic, and upstream/downstream dependencies - Experience conducting impact assessments and translating strategic requirements into technical execution plans - Familiarity with data governance frameworks, ETL processes, and documentation standards - Strong communicator who can translate technical findings into clear, business-friendly language - Detail-oriented with a commitment to data accuracy and quality - Collaborative approach to working within a matrixed, multi-stakeholder environment - Self-directed and able to manage multiple priorities in a fast-paced program Preferred Experience: - Experience with Beeline, SAP Fieldglass, or similar VMS/contingent workforce platforms - Familiarity with cloud data platforms or enterprise data hubs - Background in managed service provider (MSP) or contingent workforce programs - Experience with data migration or platform transition projects Base pay range for this position is $73,875 - $98,500 per year. Final annual compensation will be based on experience and may vary by geographic location.

• Partner directly with stakeholders across the business (Product Development, Marketing, DTC, B2B, Finance, Operations, Inventory Planning) to translate ambiguous questions into well-defined analyses, dashboards, and data products. You’ll own these end-to-end: scoping, building, validating, and communicating findings. • Build and maintain dbt models that turn raw source-system data into trustworthy, well-documented datasets. Write the tests and documentation that let both humans and AI agents downstream rely on the work. • Develop and maintain the semantic context, dashboards, and reports that the rest of the business uses to operate day-to-day. • Own metric definitions and business semantics. Drive alignment when stakeholders disagree on what a definition or number means. • Review and harden AI-generated SQL, dbt models, and Python code with the judgment to catch issues that pass tests but are semantically wrong. The majority of your output will be code you’ve collaborated on with AI agents, and you’ll bring the data intuition that makes that work trustworthy. • Investigate ambiguous data questions where the answer isn’t in the schema: talk to source-system owners, investigate edge cases, reconcile conflicting definitions, and improve our model of the business. • Help build and maintain Stio’s data infrastructure — currently Snowflake, Fivetran, dbt, GitHub, Power BI, R, and Python — and contribute to decisions about where the stack should evolve. • Improve data governance for both the Data & Analytics team and the business at large by creating documentation that’s actually useful and that AI agents can consume as context for future work. • Continuously develop your skills as the practice of data analytics evolves. This is a real part of the job, not something done on the side.