Senior Data Engineer

About the role

Fetch is looking for a Senior Data Engineer to join a cross-functional product team, working closely with machine learning engineers, backend engineers, and product managers to build robust data infrastructure that powers Fetch’s recommendation and audience targeting systems.

Responsibilities

• Design, build, and operate scalable data pipelines using batch and real-time processing technologies such as Apache Spark, Kafka, Flink, or managed cloud streaming services to process terabytes of data daily
• Build data infrastructure that ingests real-time events and stores them efficiently across databases, data warehouses, and data lakes within AWS
• Establish and enforce data contracts with backend engineering teams by implementing schema management, data quality checks, and monitoring to ensure pipeline reliability
• Make data accessible and consumable for operational services, analytics platforms, and data-intensive product features, balancing latency, freshness, and accuracy requirements
• Collaborate closely with backend engineers, machine learning engineers, and product partners to understand data access patterns, system constraints, and quality expectations
• Take ownership of significant portions of the data platform architecture, driving design decisions and technical prioritization
• Develop tools, frameworks, and recommended patterns that enable rapid development of data products and consistent pipeline deployments
• Mentor engineers on data engineering best practices and raise the overall quality bar across the organization
• Stay current with emerging technologies in data processing and infrastructure, evaluating their applicability and impact on Fetch systems

Requirements

• 6+ years of professional experience in data engineering, building and operating production data systems at scale
• Proven experience designing, building, and maintaining scalable batch and real-time data pipelines capable of processing terabytes of data daily
• Strong foundation in data architecture principles, including data modeling, schema design, and tradeoffs between latency, reliability, and cost
• Proficiency in at least one modern programming language such as Go, Python, Java, or Rust, along with strong SQL skills
• Experience with Infrastructure as Code tools such as Terraform or CloudFormation in a production environment
• Familiarity with CI/CD processes and modern software development lifecycle practices, with an emphasis on shipping incrementally and improving systems over time
• Experience implementing data quality controls, including validation, monitoring, and anomaly detection
• Ability to take ownership of projects with guidance, driving designs from initial architecture through implementation and adoption
• Comfort presenting technical designs, participating in peer reviews, and constructively challenging decisions
• Strong collaboration skills with experience working closely with software engineers, machine learning engineers, data analysts, and product partners