The company is looking to design, develop, and operate a secure, scalable, reliable, and efficient platform to facilitate the flow of data between internal and external systems supporting various departments.
Requirements
- Hands-on experience with modern data storage and processing technologies (e.g., Kafka, Postgres, blob storage, Flink, dbt, Iceberg)
- Expertise in Python and SQL; experience with other languages like Java, Scala, or Go
- Cloud-native experience in Azure, AWS, and/or Google Cloud, using container orchestration technologies like Docker, Kubernetes, and infrastructure-as-code tools like Terraform
- Familiar with DevOps best practices, using version control (Git), CI/CD (e.g., Buildkite, GitHub Actions), and monitoring and alerting (e.g., Prometheus, Grafana, Datadog)
- Experience with AI/ML, including LLMs and MCP servers
Responsibilities
- Design and develop large-scale, batch and real-time data pipelines, ELT processes, data warehouses, and data lakes, both on prem and in the cloud
- Scale our data platform to support operational growth from millions of parts per year to millions per day
- Monitor and continuously improve the performance and reliability of data connections and their impact on up-and-downstream systems, using best-in-class observability tools
- Ensure data quality and governance by managing metadata like schemas, lineage, and access control
- Collaborate with other software engineers, data analysts and scientists, other engineering disciplines, non-engineers, leadership, and vendors to understand data requirements and deliver solutions
- Stay current with emerging data technologies while recommending battle-tested right-fit solutions that align with strategic goals
- Participate in on-call rotations to maintain our SLA with the rest of the company, and prevent data issues from stalling 24/7 production schedules
Other
- Bachelor’s degree in computer science or a related field
- 8+ years of software and/or data engineering experience building and operating large-scale, distributed data systems
- Collaborate with other software engineers, data analysts and scientists, other engineering disciplines, non-engineers, leadership, and vendors to understand data requirements and deliver solutions
- Participate in on-call rotations to maintain our SLA with the rest of the company, and prevent data issues from stalling 24/7 production schedules
- Report directly to our VP of Engineering at our Everett, WA office
