Senior Software Engineer; Data

Requirements

• 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 Big Query, 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
• (Desirable) You’ve worked in startup or high-ownership environments where you wore multiple hats
• (Desirable) You’ve built or maintained embedded analytics or multi-tenant data products
• (Desirable) You’re excited about making data accessible to AI systems, whether that’s through better metadata, semantic layers, or preparing datasets for agentic workflows
• (Desirable) You care about cost optimization and data governance

• We’re looking for a Senior Data Engineer 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
• Design, build, and operate data pipelines that process terabytes of transactional data daily using Airflow/Composer and Big Query
• 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 Big Query, Cloud SQL, AlloyDB, and CDC data streams
• 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