Software Engineer

DescriptionThe Sr Software Engineer, Data Enablement is a hands-on technical engineer who builds the bridge between the Data Engineering and the AI Platform application teams as they instrument global and product events, and serves as the technical consultant who ensures each app team's independent integration work aligns with Data Enablement standards. This role spans integration engineering and quality engineering. The engineer works directly in application codebases, writes schema extensions, and builds the tooling and automation that scales onboarding across all application teams. The engineer also owns the automated test infrastructure that validates every integration before go-live, including conformance test suites, contract tests, and CI/CD quality gates. Strong communication and consulting skills run through all of this work. The engineer must explain platform standards clearly, influence technical decisions without direct authority, and guide app teams toward self-sufficiency.ResponsibilitiesWrite custom event schema extensions for each application, translating app reporting requirements into schema definitions and data contracts. Execute schema upgrade migrations, writing migration scripts and running backward-compatibility checks.Embed with application teams during integration: provide hands-on SDK implementation support, pair-program through instrumentation challenges, and debug event emission issues directly in application environments.Consult on schema design decisions, event naming conventions, and integration patterns. Review app-team-authored schemas and implementation plans to ensure alignment with platform standards. Provide technical guidance during sprint planning to prevent misalignment early.Build and maintain integration tooling, automation, and runbooks: validation scripts, schema linting tools, diagnostic utilities, troubleshooting guides, and go-live readiness checklists.Build and own automated conformance and contract test suites that validate event schema compliance, field-level data quality, and emission timing against live and staging event streams. Integrate these into application CI/CD pipelines as quality gates that catch violations before they reach the platform.Execute integration validation for each application onboarding cycle: run test suites against app event output, debug failures, and certify go-live readiness based on direct technical evidence.Build regression test suites for schema version changes, ensuring backward-compatibility across the full event catalog during major upgrades.Write SQL to validate data quality across pipeline layers and verify events land correctly through the medallion architecture. Build and maintain program-level quality dashboards reporting on test coverage, pass rates, and conformance metrics.Build internal web tooling that surfaces integration status, conformance metrics, and onboarding progress to platform stakeholders. Maintain and extend the platform SDK and developer enablement libraries.Coach app teams toward self-service integration and quality practices. Escalate to the Platform Architect only when patterns require architectural changes to the platform itself.Required Qualifications5+ years of full stack software engineering experience, with hands-on delivery across backend services and integration code (Python, Node.js, Go, or equivalent) as well as frontend tooling and internal dashboards.Strong proficiency writing and validating event schemas (JSON Schema, Avro, or Protobuf), authoring and iterating on them directly with application teams.Strong SQL skills and solid understanding of database concepts. Able to write complex queries, validate data quality across pipeline layers, and reason about data structure and flow across relational and analytical systems.Experience building automated test suites for data pipelines, event-driven systems, or API integrations, including tests that validate schema conformance, data quality, and end-to-end data flow.CI/CD pipeline experience. Able to configure test stages, integrate test runners, and build automated quality gates.Ability to manage concurrent engagements across multiple application codebases (4-5 simultaneous) while maintaining quality and context-switching effectively.Exceptional communication skills. Able to explain platform standards clearly to teams with varying technical maturity, influence decisions without direct authority, and produce runbooks, migration guides, and go-live documentation from first-hand experience.Preferred QualificationsExperience with medallion architecture (bronze/silver/gold) data platforms and how data flows through layered pipeline stages.Familiarity with Databricks, Delta Lake, Azure cloud services, or similar data infrastructure.Experience writing and executing schema migration scripts with backward-compatibility validation.Prior work in EdTech, AI/ML platforms, or multi-product SaaS environments.