Staff Software Engineer, Data Engineering

Omada Health is on a mission to inspire and engage people in lifelong health, one step at a time. They are seeking a Staff Software Engineer to lead the technical strategy and implementation of their enterprise data architecture, governance foundations, and analytics enablement tooling.

Responsibilities:

• Own the vision and technical roadmap for Omada’s enterprise data architecture, spanning ingestion, storage, modeling, and serving layers for analytics and applied statistics use cases
• Design, implement, and evolve scalable, secure, and cost‑efficient data solutions (datalakes, warehouses, marts, semantic layers) that support governed, cross‑functional analytics and self‑service
• Define and socialize architectural patterns, data contracts, and integration standards used by data and product teams across the organization
• Anticipate future needs (e.g., new product lines, new modalities, AI/ML workloads) and drive proactive architectural changes rather than reacting to incidents or point‑in‑time requests
• Lead the design of logical and physical data models to support enterprise metrics, dashboards, and ad hoc analytics, with a focus on reusability and clear ownership
• Implement robust data quality, validation, and monitoring frameworks that underpin trusted “single source of truth” definitions for core concepts (e.g., active member, MAU, GLP‑1 member)
• Partner with the Senior Product Manager, Data Enablement & Governance to translate governance decisions (definitions, ownership, change‑management processes) into concrete technical implementations in the data platform
• Set standards and review mechanisms to ensure new pipelines, marts, and reports align with enterprise definitions and governance policies
• Continuously improve performance, scalability, and cost‑efficiency of data workflows and storage; lead deep dives and remediation for complex production issues
• In close partnership with the Senior PM, define and deliver core, reusable data products (e.g., engagement, clinical, financial, client, care delivery datasets) that power dashboards, reporting, and self‑service analytics
• Co-Architect and implement technical foundations for AI‑assisted analytics tools, governed semantic layers, and reporting applications that make analysts and business users more efficient
• Partner with Product and Engineering teams owning tools like Amplitude, Tableau, and internal reporting tools to ensure consistent instrumentation, mapping to enterprise definitions, and scalable access patterns
• Translate business and product requirements into resilient schemas, data services, and interfaces that are usable, maintainable, and auditable
• Ensure production data delivery meets defined SLAs and supports downstream BI, reporting apps, and applied statistics workloads
• Play a key role in cross‑functional forums (e.g., Data Governance Committee, analytics communities) as the technical voice for feasibility, risk, and long‑term platform health
• Lead large, multi‑team technical initiatives—from design to implementation and rollout—setting a high bar for design docs, reviews, and execution quality
• Mentor senior and mid‑level engineers, elevating the team’s skills in data modeling, pipeline design, governance, and platform thinking
• Help shape playbooks for how product squads and spokes engage with central data teams on new metrics, data products, and applied stats projects
• Partner closely with Analytics, Data Science, Product, and business leaders to ensure data architecture and governance decisions are aligned with company OKRs and measurable business value
• Proactively identify complexity, duplication, and fragility in existing systems; drive simplification and standardization with sustainable solutions
• Model Omada’s values in day‑to‑day work, fostering a culture of trust, context‑seeking, bold thinking, and high‑impact delivery

Requirements:

• 8+ years of experience building, maintaining, and orchestrating scalable data platforms and high‑quality production pipelines, including significant experience in analytics or warehousing environments
• Demonstrated Staff‑level impact: leading cross‑team technical initiatives, making architectural decisions that shaped a multi‑year roadmap, and influencing stakeholders beyond your immediate team
• Deep experience with cloud data ecosystems (e.g., AWS) and modern data warehouses (e.g., Redshift, Snowflake, BigQuery), including MPP query optimization
• Strong background in data modeling for OLTP and OLAP, and designing reusable data products for BI, reporting, and advanced analytics
• Hands-on experience implementing data quality, observability, and governance frameworks, ideally in a regulated or PHI/PII‑sensitive environment
• Experience partnering with Product Management and Analytics to define and deliver platform capabilities, not just point solutions
• Strong proficiency in SQL (analytical and performance‑tuned) and experience with relational and MPP databases
• Proficiency in at least one modern programming language used in data engineering (e.g., Python, Java, Scala) and comfort applying software engineering best practices (testing, CI/CD, code review)
• Experience with workflow orchestration and data integration tools (e.g., Airflow) and event‑driven or streaming patterns where appropriate
• Familiarity with BI and analytics tools (e.g., Tableau, Amplitude, or similar) and how they integrate with governed data layers
• Experience with data governance concepts (ownership, lineage, definitions, access controls) and their technical implementation in a modern data stack
• Familiarity with AI tools for development
• Excellent communication and collaboration skills, with the ability to convey complex technical concepts to non‑technical stakeholders
• Highly self‑directed and comfortable operating in ambiguous, cross‑functional problem spaces, creating clarity and direction where none exists
• Strong sense of ownership and bias for impact; you care about outcomes for members, customers, and internal users, not just elegant systems