- Help shape how engineers, analysts, and business teams build on and use our enterprise data platform
- You’ll design data products and the self-service experiences around them — from the data model to the APIs and workflows producers and consumers rely on — so teams can get what they need without waiting on tickets
- You’ll also help build the enterprise data context that lets people and AI find, understand, and trust data
- This role suits a hands‑on data engineer with strong data modeling, AWS, and Python skills who enjoys owning a problem from the user’s need down to the data underneath
- Design data models and domain‑driven building blocks that turn raw data into reusable, well‑governed data products for end consumers
- Contribute to the enterprise data context — semantic models, ontologies, and knowledge bases that make data discoverable and usable by people and AI agents
- Build end‑to‑end self‑service experiences for data producers and consumers, including onboarding, SQL automation, data quality monitoring, and the APIs and workflows that expose data products
- Build and evolve AI‑assisted and agentic automation that removes manual work, including migration support, impact assessment, and guided workflows for platform and data teams
- Own incident response for the services you build: lead root‑cause analysis and after‑action reviews, ship durable fixes,



and write runbooks so first‑line support can resolve recurring issues on their own
- Drive priorities for Platform UX services in partnership with engineering leadership and teams across US and India time zones: turn user needs into a prioritized backlog, weigh trade‑offs, unblock users, and own the outcomes of what you deliver

- Solid data modeling and data architecture skills, including domain‑driven design and building reusable data products for downstream consumers
- 7+ years in data engineering, data platform engineering, or software engineering
- Designing modular, reusable platform patterns — frameworks, plugins, or marketplaces — that scale automation across many teams
- Hands‑on experience with AWS (S3, Lambda, Glue, Lake Formation, Redshift, API Gateway), lakehouse architectures and Apache Iceberg in production, and orchestration with Apache Airflo
- Building self‑service data experiences — APIs, workflows, or tooling that let producers and consumers work independently
- 5+ years of professional Python, building APIs, automation, and data or platform tooling, with the ability to troubleshoot distributed data systems
- Production experience building agentic or AI‑assisted workflows for analytics, migration, or platform enablement, including semantic layers, ontologies, or knowledge graphs/knowledge bases for enterprise data
- Experience with data quality frameworks, data governance, or access management

📌 Senior Software Development Engineer (Ottawa)
🏢 GoDaddy
📍 Ottawa