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’s data platform is a critical foundation for decision-making and product innovation. As a Senior Data Platform Engineer, you’ll take an architectural and prescriptive role in shaping how data is stored, processed, and orchestrated across the company. This role owns key platform abstractions and standards, particularly around Iceberg-backed data storage, data contracts, and orchestration patterns. You’ll apply deep technical judgment to guide platform evolution, mentor engineers, and ensure the data platform scales safely and predictably.

This is a highly impactful role for engineers who thrive at the intersection of distributed data systems, platform engineering, and software architecture.

What You’ll Do:

Own Core Data Platform Architecture

Design and evolve platform components built on Iceberg-backed data storage. Define how data platform services are structured, composed, and consumed across teams. Take a prescriptive, system-level approach to platform design to reduce fragmentation and complexity.

Define & Enforce Data Contracts

Establish standards for data schemas, ownership, and lifecycle management. Build mechanisms to validate and enforce contracts across ingestion and downstream consumers.

Orchestration & Workflow Design

Design and own orchestration patterns within the internal data platform service. Guide how distributed processing workloads (e.g., Spark-based jobs) are scheduled, retried, and monitored.

Reliability, Scalability & Cost Awareness

Improve platform resilience, failure isolation, and recovery patterns. Partner with Finance and Engineering to improve cost visibility and efficiency of data workloads.

Mentorship & Technical Leadership

Mentor Data Platform Engineers and raise the technical bar across the platform team. Review designs, guide implementation decisions, and influence long-term platform strategy.

Cross-Functional Influence

Collaborate with Product, Analytics, ML, and Infrastructure teams to align data platform capabilities with business needs. Act as a trusted technical partner for high-impact data initiatives.

AI Fluency in Platform Engineering

Integrate AI-assisted tooling into data platform workflows to accelerate design, validation, and troubleshooting. Evaluate emerging AI tools for data and platform engineering, balancing speed with reliability, security, and correctness.

Minimum Qualifications

5+ years of experience in data platform, data engineering, or platform engineering roles, with demonstrated ownership of complex systems. Deep expertise in AWS-based data architectures and cloud-native system design. Deep experience designing and operating distributed data processing systems (e.g., Spark at scale, batch and streaming workloads). Strong software engineering fundamentals with proficiency in Python, Java, or Scala, applied to large, production-grade systems. Proven ability to design, build, and own CI/CD pipelines, infrastructure, and production operations for critical platform systems. Demonstrated ability to debug complex, cross-system issues, influence technical decisions, and mentor engineers. Experience using AI-assisted tools thoughtfully to improve engineering outcomes, code quality, and system reliability. Preferred Qualifications Deep hands-on experience with AWS data services (e.g., S3, Glue, EMR, Kinesis, MSK) in production environments. Strong experience with data orchestration frameworks and workflow engines, including design or operational ownership. Experience defining and improving data observability standards, monitoring strategies, and operational metrics. Experience owning broader platform or distributed systems domains, including setting standards or paved paths for multiple teams. Track record of improving developer velocity, reliability, and platform adoption across multiple teams.

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

Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is [INSERT RANGE]. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.