About the role
Narvar is growing! We’re 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. We’re looking for a Senior Software Engineer, Data to own and evolve the pipelines, platforms, and data products that power Narvar’s analytics, ML, and merchant-facing products. You’ll work across the full stack of our data infrastructure, from ingestion and transformation to the analytics surfaces our merchants use every day. You’ll 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 We’re Looking For We care about judgment and ownership over credentials. You’re likely a strong fit if you: Have 5–8 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 You’ll Thrive Here These aren’t hard
