Data Platform Engineer

2/1/2026

As a Data Platform Engineer, you will build and operate reliable data ingestion pipelines and core platform services. You will partner with product, analytics, and engineering teams to ensure data is ingested, processed, and made available reliably.

Working Hours

40 hours/week

Company Size

501-1,000 employees

Language

English

Visa Sponsorship

About The Company

Fetch, America's Rewards App, empowers consumers to Live Rewarded and helps brands create lifelong customers through the power of Fetch Points. Fetch has sweeping visibility into what consumers buy, capturing more than $179 billion worth of transactions annually using cutting-edge artificial intelligence and machine learning technologies. To date, Fetch users have submitted more than 5 billion receipts and earned more than $1 billion in rewards. The app is available to download on the App Store and Google Play Store and has more than 6 million five-star reviews from happy Fetchers.

About the Role

Meet Fetch Engineering:

At Fetch, our engineering philosophy emphasizes innovation, adaptability, and informed decision-making. Our engineers thrive in complex environments, making decisions based on critical thinking and data, even in uncertain situations. We value proactive problem-solving and focus on driving impactful results while maintaining high technical standards. You will work alongside talented engineers who are dedicated to pushing the boundaries of technology and encouraging each other to excel. We understand that Fetch may not be the right fit for everyone, but if you're passionate about solving challenging problems and navigating intricate systems, Fetch could be a great place for you.

About the Role:

Fetch is building a modern, cloud-native data platform that powers analytics, experimentation, and machine learning across the company. As a Data Platform Engineer, you’ll focus on building and operating reliable data ingestion pipelines and core platform services that enable teams to work with data at scale.

This role is ideal for engineers who enjoy hands-on execution, learning distributed systems, and growing their platform engineering skill set while working closely with senior engineers on complex systems.

You’ll partner with product, analytics, and engineering teams to ensure data is ingested, processed, and made available reliably, while maintaining strong operational excellence across the platform.

This is a full-time role that can be held from one of our US offices or remotely in the United States.

What You’ll Do:

Build & Operate Data Pipelines

Design, implement, and maintain data ingestion pipelines using AWS-native data tools and distributed processing frameworks.
Support batch and streaming ingestion patterns with a focus on reliability, scalability, and observability.

Platform Operations & Reliability

Operate and improve core data platform services, addressing incidents, performance issues, and operational toil.
Implement monitoring, alerting, and runbooks to improve platform stability and on-call readiness.

Distributed Systems Support

Work with distributed data processing systems (e.g., Spark-based workloads) and orchestration frameworks.
Debug production issues across compute, storage, and networking layers.

Infrastructure & Automation

Contribute to Infrastructure as Code (Terraform, CloudFormation, or CDK) and CI/CD workflows.
Help improve automation around deployments, scaling, and platform maintenance.

Cross-Team Collaboration

Partner with data producers and consumers to onboard pipelines, troubleshoot issues, and improve platform usability.
Learn and apply platform standards and best practices defined by senior engineers.

AI-Assisted Engineering

Use AI-assisted tools to accelerate development, troubleshoot issues, and validate infrastructure or pipeline code—while ensuring correctness, security, and performance through testing and review.

Minimum Qualifications

3+ years of experience in data platform, data engineering, or platform engineering roles.
Experience working with AWS and cloud-based data tooling.
Familiarity with distributed data processing concepts (e.g., Spark, batch and/or streaming systems).
Proficiency in at least one programming language (Python, Java, Go, or Scala preferred).
Experience with CI/CD, Infrastructure as Code, or operating production systems.
Ability to learn quickly, debug complex systems, and collaborate effectively across teams.
Experience using AI-assisted development tools responsibly to improve development speed and quality.

Preferred Qualifications

Hands-on experience with AWS data services (e.g., S3, Glue, EMR, Kinesis, MSK).
Exposure to data orchestration frameworks or workflow engines (e.g., Airflow, Step Functions).
Familiarity with data observability, monitoring, or operational metrics.
Interest in growing ownership across platform or distributed systems domains.

Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.

Key Skills

Data EngineeringAWSDistributed SystemsPythonJavaGoScalaCI/CDInfrastructure as CodeMonitoringDebuggingAutomationCollaborationAI-Assisted ToolsData PipelinesObservability