Narvar is growing! Were building the data infrastructure behind the post-purchase experiences of hundreds of millions of consumers. When a shopper tracks a package, initiates a return, or gets a delivery notification through one of our 1,500+ brand partners, our data systems are doing the work behind the scenes. Were looking for a Senior Software Engineer, Data to own and evolve the pipelines, platforms, and data products that power Narvars analytics, ML, and merchant-facing products.
Youll work across the full stack of our data infrastructure, from ingestion and transformation to the analytics surfaces our merchants use every day. Youll make architectural decisions, ship production systems at scale, and we expect you to work in an AI-native way, using agentic coding tools to increase your leverage and ship faster.
For this role, you can be located in Canada and able to work within EST/EDT hours. We are fully remote.
Day-to-day
- Design, build, and operate data pipelines that process terabytes of transactional data daily using Airflow/Composer and BigQuery
- Own end-to-end data models and transformations that power merchant analytics, operational reporting, and ML features
- Build and maintain embedded analytics infrastructure the data products our merchants interact with directly
- Evolve our data platform on GCP, including BigQuery, Cloud SQL, AlloyDB, and CDC datastreams
- Improve data quality and reliability through testing, observability, alerting, and validation frameworks
- Own data lineage, metadata, and documentation, and help prepare our data layer for agentic and LLM-powered use cases with semantic clarity and standardized metric definitions
- Collaborate cross-functionally with product, ML, and GTM teams, and contribute to technical direction through design docs and architecture decisions
What Were Looking For
We care about judgment and ownership over credentials.
Youre likely a strong fit if you:
- Have 58 years of experience building and operating production data systems
- Have strong SQL skills and are proficient in Python, with flexibility to pick up other languages as needed. Comfortable building and maintaining APIs.
- Have worked with modern data stacks on cloud platforms (GCP preferred, but AWS or Azure transfers well), including cloud data warehouses like BigQuery, ELT patterns, and orchestration with Airflow
- Understand data modeling deeply dimensional modeling, slowly changing dimensions, incremental processing
- Treat data quality, lineage, and observability as first-class engineering concerns
- Communicate clearly with technical and non-technical stakeholders and are comfortable working cross-functionally
- Already use AI and agentic coding tools as a core part of how you work for planning, code generation, debugging, and code review.
Signals That Youll Thrive Here
These arent hard requirements, but strong indicators:
- Youve worked in startup or high-ownership environments where you wore multiple hats
- Youve built or maintained embedded analytics or multi-tenant data products
- Youre excited about making data accessible to AI systems, whether thats through better metadata, semantic layers, or preparing datasets for agentic workflows
- You care about cost optimization and data governance
Why Data Engineering at Narvar?
Because post-purchase is one of the most >Please read our Privacy Policy to learn what personal information we collect in connection with your job application, and how we may use and share it.
