Remote data engineer role for analytics and machine learning platforms at Gopuff with a salary up to $148,000

Gopuff, an instant-needs consumer goods delivery platform founded in 2013, has opened applications for a fully remote Data Engineer position. Placing data at the core of its operational strategy for managing its digital platform, the company is seeking an engineer to design, build, and scale data systems that power analytical insights, operational experimentation, and machine learning models across its business units, with an application deadline of September 15, 2026.

Data pipeline architecture and infrastructure modernisation

The scope of this role encompasses designing, building, and maintaining scalable batch and real-time data pipelines that feed analytics platforms, experimentation frameworks, and machine learning applications. The role requires direct contributions to data platform architecture and maintenance to ensure cost efficiency, low latency, and scalability, alongside close collaboration with analytics, product, engineering, and operations teams to deliver accurate data solutions that drive commercial and operational performance. The engineer will also construct and refine structured datasets to serve as authoritative sources of truth across the organisation, while elevating standards for data quality, reliability, and lineage through testing, monitoring, incident documentation, and response best practices, as well as advancing team tooling and CI/CD pipelines.

Technical requirements and experience

The company specifies three to five years of experience in data engineering or software engineering, with a practical focus on building and scaling modern data platforms. The role requires advanced proficiency in Python and SQL, along with hands-on experience working with cloud data warehouses and data lakes such as Snowflake, BigQuery, or Databricks. Core technical competencies include constructing batch data pipelines using DAG-based orchestrators like Dagster or Airflow, working with event-driven architectures and real-time streaming via Kafka, Kinesis, or Event Hubs, and leveraging stream processing frameworks such as Apache Beam, Flink, or Spark Streaming. The responsibilities also require advanced knowledge of deploying services and applications across Kubernetes environments using tools such as ArgoCD, Helm, or Istio, alongside implementing infrastructure as code via Terraform.

Salary details and benefits package

The company has set the base annual salary range for this remote position between $118,000 and $148,000, with the final offer determined by candidate skills, experience, interview performance, and market conditions. The successful candidate is eligible for an annual discretionary cash bonus and participation in the company's equity incentive plan. The benefits package includes comprehensive medical, dental, and vision coverage, a retirement savings plan, short-term and long-term disability insurance, mental health support programs, fitness stipends, flexible paid time off, a 25 percent discount on company products with membership, and an employee assistance program.

This role targets technical talent capable of bridging systems engineering requirements with the needs of analytics and product teams, particularly in managing large-scale data streams, maintaining distributed cloud reliability, and rapidly resolving data quality issues. Candidates with the required skills in cloud data platform development and real-time streaming tools can align their profiles with the job requirements and apply through the official job listing before the stated deadline.