Data Platform Engineer at Fetch

, , United States -

Full Time

Start Date

Immediate

Expiry Date

02 May, 26

Salary

0.0

Posted On

01 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, AWS, Distributed Systems, Python, Java, Go, Scala, CI/CD, Infrastructure as Code, Monitoring, Debugging, Automation, Collaboration, AI-Assisted Tools, Data Pipelines, Observability

Industry

technology;Information and Internet

Description

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.

Responsibilities

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.