virtahealth - Senior Software Engineer II

• Design and own the data contracts and processing semantics that make identity, deployment context, eligibility, audience attributes, deduplication, and field persistence explicit and testable across the data lifecycle. • Build end-to-end observability and reconciliation that explains how source records become downstream outcomes — including data freshness, expected filtering, rejected records, deduplication, safe replay, and repair of historical state. • Lead technical discovery and delivery of high-impact work across Member Marketing and Coverage Eligibility, collaborating closely with Product, data, and external partners. • Partner with Product and Growth stakeholders to translate evolving audience and workflow requirements into reusable platform capabilities, keeping business policy cleanly separated from technical implementation. • Design for correctness and auditability in regulated workflows, including data provenance, consent and suppression controls, rollback, replay, and safeguards against incorrect or cross-customer data use. • Modernize legacy, file-based processes toward well-contracted, event-driven integrations with strong observability, resilience, and security. • Own systems end-to-end — from architecture through operations — driving improvements in reliability, partner experience, and long-term maintainability. • Apply an experiment mindset (Build-Measure-Learn) to validate assumptions and focus on outcomes over output, using AI-assisted tooling where it improves speed and quality without compromising correctness. • FIRST 30 DAYS: LEARN & CONNECT • Understand Virta’s data ecosystem — architecture, key data flows, systems for Coverage Eligibility and Member Marketing, and how partners interact with Virta’s platform. • Get familiar with existing processes and pain points around file-based exchanges, partner onboarding, data quality, and incident patterns. • Build relationships with key stakeholders: engineering teammates, product managers, the data team, and partner-facing roles. • Observe real-world partner data issues, reviewing tickets, Slack threads, and postmortems to identify recurring themes. • DAYS 31–60: CONTRIBUTE & EXPERIMENT • Ship production code: contribute meaningfully to an in-flight initiative touching data flows or partner integrations. • Identify and propose a targeted improvement using the Build-Measure-Learn loop — e.g., automating a partner data-quality check or prototyping stage-level reconciliation. • Start building technical credibility across the team by writing clean, scalable code and actively participating in design reviews. • DAYS 61–90: LEAD & SHAPE • Own a meaningful workstream — such as a small net-new service, a platform capability (e.g., data validation or status tracking), or a cleanup/migration effort. • Drive an architectural discussion that involves tradeoffs across scalability, observability, and correctness. • Show thought leadership by pushing forward better patterns (e.g., eventing over polling, stronger test coverage, clearer data contracts). • Build trust through delivery — others should be seeking your input and starting to rely on you as a technical thought partner. • Strong backend engineering skills, with a track record of building and operating scalable, reliable systems in production — ideally involving APIs, event-driven architectures, or data integrations. • Experience designing data-intensive systems where correctness depends on explicit schemas, identity or entity resolution, incremental processing, idempotency, lineage, reconciliation, and recovery from partial failure. • A proactive, ownership-first mindset — you don’t wait for direction; you surface problems, propose solutions, and drive them to completion. • High agency and autonomy — able to navigate ambiguity, set direction, and execute independently while keeping stakeholders aligned. • Demonstrated technical leadership — able to establish architecture and engineering standards across team boundaries, mentor senior engineers, and turn ambiguous business problems into a sequenced technical roadmap. • Experience with B2B or partner-facing data systems, such as file-based integrations, real-time data exchanges, or partner APIs. • Sound judgment about AI-assisted tooling — where it improves engineering velocity, data-quality investigation, documentation, and operations, and where deterministic controls are required for correctness and safety. • Strong collaboration and communication skills, especially in cross-functional environments involving Product, data, and external partners. • Typically 10 + years of software engineering experience, with demonstrated ability to operate at a senior level. • Experience in healthcare data domains, such as eligibility, claims, EHR, or member marketing — especially in regulated or partner-integrated environments. • Experience with customer-data, marketing-automation, or audience-activation platforms such as Braze, Segment, Salesforce Marketing Cloud, or comparable systems. • Prior work modernizing legacy data flows, including migrations from SFTP/file-based systems to API- or event-driven architectures. • Familiarity with data quality frameworks, lineage tracking, or automated anomaly detection in data pipelines. • Demonstrated use of AI/LLM-based tooling in engineering work — e.g., for test generation, documentation, data mapping, or observability. • Previous roles where you've had to influence without formal authority, or drive change across teams or systems you didn’t own directly. • We don’t expect candidates to know everything on day one, but here are some of the tools we currently use day-to-day: • Cloud & Infrastructure • Google Cloud Platform: GKE (Kubernetes), Workflows, Pub/Sub, BigQuery, CloudSQL, Memorystore, Gemini • Data & Modeling • SQL, BigQuery, dbt, data contracts, lineage, reconciliation, and data-quality testing • Dev & Collaboration • GitHub + GitHub Actions for CI/CD • Google Workspace for docs, specs, and async collaboration • ChatGPT + OpenAI platform to accelerate development, testing, documentation, and product use cases • Languages & Tooling • Golang (primary language for backend services) • Python (for data tooling, automation, AI workflows) • JavaScript/TypeScript (for internal tools and platform UIs) • VALUES-DRIVEN CULTURE • Virta’s company values drive our culture, so you’ll do well if: • You put people first and take care of yourself, your peers, and our patients equally • You have a strong sense of ownership and take initiative while empowering others to do the same • You prioritize positive impact over busy work • You have no ego and understand that everyone has something to bring to the table regardless of experience • You appreciate transparency and promote trust and empowerment through open access of information • You are evidence-based and prioritize data and science over seniority or dogma • You take risks and rapidly iterate • Is this role not quite what you're looking for? Join our Talent Community https://jobs.ashbyhq.com/virtahealth/form/talent-community-form and follow us on Linkedin https://www.linkedin.com/company/virta-health to stay connected! • All jobs except Health Coaches ← delete before posting