Data Engineer

Role Highlights

Infrastructure as Code

Own and modularize the infrastructure behind Seer's data platform in Terraform or OpenTofu, mapping what exists today and designing what it needs to become

Manage permissions and access across the platform, including how team members and agents securely reach data through tools like the Seer’s agentic tooling.

Cloud Platform

Build and maintain cloud services behind our data products, including BigQuery, Cloud Run, Cloud Functions, Cloud Storage, making the cost and reliability tradeoffs that let us scale without supprises

Automate the processes that bring new clients, data sources, and reports into the platform so they flow through without manual intervention

CI/CD and Code Quality

Design and maintain GitHub Action pipelines with automated tests, multi-stage deploys, and review gates

Take part in pull requests and code review across the engineering team, raising the quality bar for all changes

Reliability and Observability

Build the alerting, monitoring, and logging systems that provide insight to the platform’s health, and own what happens when something breaks

Define KPIs for the processes you build and set the thresholds that tell us when it's time to review,audit or retire tooling

AI-Powered Engineering

Integrate Claude Code, Codex, and other coding agents into your daily engineering workflows to design, implement, test, and maintain production systems, with clear ownership of code quality, security, and reliability

Collaboration

Partner with the Data Engineering Leads and the Director of Engineering to turn platform needs into a roadmap you help shape

Work from requirements gathered by our product and project managers, so your focus stays on building, not on client meetings

Essential Skills

You have hands-on experience writing and modularizing infrastructure as code with Terraform or OpenTofu

You have deep familiarity with GitHub, including pull requests, code review, and building workflows with GitHub Actions

You have built and run production infrastructure on **GCP **or AWS

You have strong programming skills in an object-oriented language such as Python, or TypeScript

You have experience designing alerting and monitoring structures, and you understand what it means to own a system when it fails

You have a strong working knowledge of **SQL **and relational databases

You are comfortable in the weeds and prefer owning infrastructure yourself over relying on a separate team to handle it

You are someone who defines what "good" looks like for a process, sets KPIs against it, and holds yourself accountable to them

You feel energized by building something early-stage and helping decide what it becomes as well as overhauling legacy systems to improve stability and functionality

Bonus!

You have experience with object-relational mapping (ORM) tools

You have built your own AI agents, skills, or workflows to write and review code faster

You have worked in an agency, a startup, in a marketing technology or SaaS company

You have been part of an on-call rotation for production systems

This might not be the right role for you if...

You're used to a separate DevOps or platform team handling infrastructure for you

You'd rather hand a system off once it ships than own its lifecycle

You prefer a mature platform with defined processes over helping to design and build one

You see AI as hype rather than a practical tool

30/60/90 Day Plan

First 30 Days: Learn

Complete division training and get oriented in our GCP environment, Terraform codebase, and GitHub workflows

Map the current state of platform infrastructure and flag the first gaps you'd close

Ship your first reviewed pull request through our CI/CD pipeline

60 Days: Build

Own the design and delivery of an infrastructure improvement end to end, such as a module refactor or a new platform component

Add or improve alerting for a critical pipeline, with defined KPIs for what healthy looks like

90 Days: Lead

Operate independently on platform requests, bringing solutions, not just questions

Deliver a visible, scalable improvement to the platform, such as automated client onboarding or bringing a manual area under infrastructure as code

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