Data Engineer at Gopuff

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 Data Engineer to design, build, and scale the data systems that power insights, experimentation, and operational excellence across the company.

About the Role

We are hiring a Senior Data Engineer on a Full Time basis. In this position you will 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. 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.

Key Responsibilities

• 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 teams to deliver high-quality data solutions that drive measurable business impact.

Requirements

We are looking for candidates with 3-5 years of experience in data engineering or software engineering with a strong focus on data platform development. You should bring proven experience building and scaling modern data platforms and delivering high-impact data solutions. Strong communication skills and the ability to work closely with both technical and non-technical partners are essential, along with a passion for building reliable, accessible, and high-quality data products.

Technical expertise required includes strong proficiency in Python and SQL, experience with modern cloud data warehouses and lakes such as Snowflake, BigQuery, and Databricks, and experience building batch pipelines using DAG-based orchestrators such as Dagster or Airflow. Candidates should also have experience with event-driven architectures using Kafka, real-time or streaming pipelines using Apache Beam, Flink, or Spark Streaming, deploying applications and services to Kubernetes with tools such as ArgoCD, Helm, or Istio, implementing DevOps concepts within data workflows including CI/CD, observability, monitoring, and lineage, and working with Infrastructure-as-Code tools such as Terraform.

Location

This role is fully remote and open to candidates located anywhere.

Compensation and Benefits

The remote base salary range for this position is $118,000 - $148,000. This role is eligible for a discretionary annual cash bonus and participation in our equity incentive plan. Additional benefits include medical, dental, and vision insurance, a 401(k) retirement savings plan, HSA or FSA eligibility, long and short-term disability insurance, mental health benefits, a fitness reimbursement program, a 25% employee discount and FAM Membership, flexible PTO, group life insurance, and an employee assistance program through AllOne Health.