Senior Data Engineer, Gopuff

• This is a highly technical, hands-on role for an engineer who wants to solve complex data problems at scale and directly influence business outcomes
• Strong proficiency in Python and SQL
• Experience with modern cloud data warehouses and lakes (e.g., Snowflake, BigQuery, Databricks)
• Experience building batch pipelines using DAG-based orchestrators (e.g., Dagster, Airflow)
• Experience with event-driven architectures using Kafka, Kinesis, or Event Hubs
• Experience developing real-time or streaming pipelines using Apache Beam, Flink, or Spark Streaming
• Experience deploying applications and services to Kubernetes and using tools such as ArgoCD, Helm or Istio
• Experience implementing DevOps concepts within data workflows (CI/CD, observability, monitoring, lineage)
• Experience with Infrastructure-as-Code (e.g., Terraform)

Desirable

• At Gopuff, data sits at the heart of our strategy. We are reimagining how people purchase everyday essentials, from snacks to household goods to alcohol, all delivered in minutes
• To fuel this mission, we are seeking a Senior Data Engineer to design, build, and scale the data systems that power insights, experimentation, and operational excellence across the company
• As a Senior Data Engineer, you will play a critical role in shaping Gopuff’s modern data platform
• You’ll architect reliable pipelines, create insights ready data products, and collaborate closely with analytics, product, and engineering teams to ensure data is trustworthy, discoverable, and ready for action
• Design, build, and maintain scalable batch and real-time data pipelines that power analytics, experimentation, and machine learning
• Contribute to the architecture and maintenance of the Data Platform, ensuring systems are performant, cost-efficient and scalable
• Partner cross-functionally with analytics, product, engineering and operations to deliver high-quality data solutions that drive measurable business impact
• Develop and maintain curated, well-modeled datasets that serve as trusted sources of truth across the organization
• Champion data quality, reliability, and observability by implementing best practices in testing, monitoring, lineage, and incident response
• Mentor junior engineers and contribute to team standards, patterns, and best practices
• Drive improvements to infrastructure, developer workflows, CI/CD, and data platform tooling