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Data Engineer – Gopuff
Location: Remote (United States)
Employment Type: Full-Time
Compensation: $118,000 – $148,000 USD Base Salary + Discretionary Cash Bonus + Equity
Department: Data Platform & Analytics Engineering
Industry: E-Commerce, Quick Commerce, Hyper-Local Logistics
About Gopuff
Gopuff is a leading quick-commerce platform redefining instant delivery for everyday essentials—from snacks and drinks to cleaning supplies and OTC medications—delivered in minutes. Operating micro-fulfilment centres across hundreds of markets, Gopuff combines proprietary inventory management, predictive logistics, and real-time order routing to power seamless customer experiences.
About the Role
Gopuff is seeking an experienced, highly technical Data Engineer to shape and scale our modern enterprise data platform. Data sits at the center of Gopuff’s operating model—driving everything from dynamic pricing, inventory forecasting, and micro-fulfilment logistics to marketing experimentation.
In this role, you will build robust batch and real-time streaming pipelines, develop curated data products, and implement modern DataOps patterns across cloud data warehouses, event hubs, and Kubernetes infrastructure.
Key Responsibilities
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Pipeline Architecture: Design, deploy, and maintain scalable batch and low-latency streaming pipelines powering core analytics, ML models, and operational dashboards.
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Data Platform Scaling: Optimize cloud data lakes and warehouses (Snowflake, BigQuery, Databricks) for performance, query efficiency, and storage cost management.
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Real-Time Data Streaming: Build event-driven streaming solutions using Kafka, Kinesis, Apache Flink, Spark Streaming, or Apache Beam.
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Orchestration & DataOps: Develop DAG-based workflows using Dagster or Apache Airflow. Enforce continuous integration, automated testing, continuous delivery (CI/CD), and observability.
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Kubernetes & Infrastructure as Code: Deploy data processing microservices to Kubernetes using Helm, ArgoCD, or Istio, and provision cloud resources via Terraform.
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Cross-Functional Collaboration: Partner with analytics engineers, product managers, and software teams to construct reliable, discoverable, single-source-of-truth datasets.
Technical Qualifications & Profile
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Professional Experience: 3–5 years of hands-on data engineering or software engineering experience focused on data platform development.
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Core Programming Languages: Advanced proficiency in Python and SQL.
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Cloud & Warehousing: Hands-on experience with modern platforms (Snowflake, Databricks, or Google BigQuery).
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Streaming & Event Systems: Experience building event-driven streaming architectures using Kafka, Kinesis, Event Hubs, Flink, or Spark Streaming.
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Containerization & IaC: Familiarity with Kubernetes, ArgoCD, Helm, and Infrastructure-as-Code tools like Terraform.
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Orchestration: Experience designing workflows in Dagster or Apache Airflow.
Compensation & Benefits Overview
| Attribute | Details |
| Job Title | Data Engineer |
| Company | Gopuff |
| Work Location | Remote (United States) |
| Base Salary | $118,000 – $148,000 USD |
| Additional Pay | Annual Discretionary Cash Bonus + Equity Incentive Plan |
| Core Benefits | Flexible PTO, Medical/Dental/Vision, 401(k), HSA/FSA, Mental Health Benefits, 25% Employee Discount & FAM Membership |


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