Senior Data Engineer

This is a fully remote position, open to applicants in California, +18 more states.

📋 Description

• Develop and manage data pipelines.

• Create and implement pipelines that facilitate data movement across various systems, including ingestion, transformation, compliance, and cross-domain data flows.

• Take ownership of pipeline operations from start to finish: monitoring, resolving incidents, and ensuring data quality across both new and existing workloads.

• Make independent and informed design choices for pipelines while adhering to the architecture established by the team.

• Evaluate and enhance existing data systems.

• Acquire a solid understanding of how the current infrastructure integrates by mapping data flows, dependencies, and performance metrics.

• Enhance documentation, observability, data quality, and operational standards within the systems you engage with.

• Recognize technical debt and reliability risks, providing recommendations that have a significant impact.

• Construct and sustain data infrastructure.

• Provision and oversee the infrastructure required for your data workloads, adhering to established Infrastructure as Code (IaC) practices and team standards.

• Participate in shared infrastructure as the platform evolves, building on new foundations as they become accessible.

• Ensure the reliability, performance, and cost-effectiveness of the infrastructure you manage.

• Collaborate across the data platform.

• Acquire sufficient knowledge of the team's entire system footprint to assist when priorities change or team members are unavailable.

• Support platform initiatives as necessary—you won't be solely responsible for new builds, but should be prepared to assist when the team requires flexibility.

⛳️ Requirements

• 6–8+ years of experience in data engineering with direct responsibility for production systems.

• Proficient in pipeline design and orchestration within a production setting.

• Advanced SQL skills: capable of complex transformations, performance tuning, and debugging in a cloud data lake or warehouse environment.

• Strong proficiency in Python: producing production-grade code, scripting, testing, and debugging.

• Familiarity with infrastructure-as-code for the provisioning and management of cloud data resources.

• Knowledge of AWS data infrastructure, including S3, IAM, and relevant managed services.

• Experience in inheriting and enhancing systems that you did not create—gaining understanding, identifying risks, and driving improvements.

• Excellent written communication skills: able to document systems, processes, or recommendations for others to act upon independently.

• Comfortable working across team boundaries with engineering and product departments to meet data needs.

• Experience utilizing AI-assisted development tools (such as Claude Code, Cursor, Copilot, or similar) to streamline engineering workflows.

• Nice to have:

• A background in data science or analytics—familiar with model inputs and outputs, statistical concepts, and supporting analytical or decision-support workflows.

• Experience with dbt or similar transformation frameworks: capable of reading models, understanding grain and dependencies, and writing tests.

• Familiarity with managed ELT tools (such as Fivetran, Stitch, or similar).

• Experience in a regulated industry (healthcare, insurance, financial services) with an understanding of compliance-driven data requirements.

• Experience with SaaS platforms, particularly in multi-tenant data architectures.

🏝️ Benefits

• Check out our benefits here!