Senior Software Engineer, Data

🕒 July 3

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Narvar

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2012

📦 Logistics

📣 Marketing

💼 Consulting

💰 $30M Series C on 2018-08

Logistics • Marketing • Consulting

Narvar is a company that specializes in creating intelligent post-purchase experiences for ecommerce businesses. Their platform provides a range of services to enhance customer engagement and retention, from setting clear delivery expectations and proactive multi-channel messaging to seamless returns and exchanges. Narvar's solutions are designed to build loyalty by personalizing the consumer journey and optimizing reverse logistics, ultimately converting and retaining customers while increasing revenue and reducing costs. The company boasts a powerful network and integrations with popular platforms like Shopify, Zendesk, and Salesforce, and supports over 2,000 retailers globally. Narvar's services cater to a variety of industries including apparel, electronics, and beauty, providing exceptional post-purchase experiences through actionable insights and data-driven interactions across their ecosystem.

📋 Description

• 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

🎯 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 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.