Are you a talented and driven platform engineer who’s ready to operate at a broader scale - defining strategy, aligning cross-functional stakeholders, and setting the bar for data platform engineering across an org? Can you wrangle a CTE with DBT and ELT like you would a BLT? (that last one is a sandwich) Does tech debt quiver in its boots at the sound of your name? Do you butter your bread with evented systems? Have the letters C, Q, R, and S been ruined for you in an eventually consistent manner? If so, we’ve got news for you: you’re not alone!
We are building a best-in-class Data practice and looking for a Data Platform Engineer to join our Platform Engineering org, and partner with our Data Science, and broader engineering teams. Our work is broad and varied, collecting data on how our product works (e.g. user needs, product friction, product adoption across multiple user personas), understanding how our business works (helping provide the platform that forecasts key outcomes, builds strategic KPIs), empowering our go-to-market motions (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. While we have built out a solid data lake/warehouse, now we're scaling its impact and reliability while enabling faster, more strategic decision-making.
You’ll help shape our vision for the data platform, influence org-wide architectural decisions, and serve as a technical leader across multiple domains. You’ll work alongside some of the best Platform Engineers - think SRE meets Ops, with a strong focus on automation, scale, and empathy. Your teammates are talented folks who value code that is 80% of the value for 20% of the work, designs that are forward-thinking enough to be easily flexible for the next features, and leadership with a healthy dose of mindfulness and humility.
Data at Apollo will be challenging. First, any type of user may be engaged across a wide surface area of products, spanning their CLI, code editors, as well as Apollo’s logged-in experience, integration points, collaboration workflows, and more. Second, the notion of success changes over time for our users, spanning from creating a rich local development experience, to building a proof-of-concept, to scaling their supergraph across the entire organization, utilizing Apollo Router in production use cases and ensuring performance and reliability across thousands of services. Third, when organizations adopt GraphOS, it often leads to a fundamental reshaping of how teams work together, and we believe there are ways to help customers be 10x more effective in this transformation.
What You'll Do
Become a key technical leader on the team, taking responsibility for the success of various subsystems.
Own complex projects from problem framing through execution, often across multiple teams.
Raise the technical bar through mentoring, design reviews, and hands-on collaboration.
Create technical designs that proactively address cost efficiency, security, and observability.
Deliver technical plans, one-pagers, DRs, and other artifacts.
Work with tools and technologies like BigQuery, Airflow, Kafka, DBT, Fivetran, Hashboard, Hightouch, Kubernetes, GCP, Helm, Terraform, DataDog, ArgoCD, CircleCI, Atlantis, Docker (and more) to deliver your work.
Drive measurable improvements in data reliability, discoverability, and usability.
Participate in an on-call rotation as necessary.
What You Bring
7+ years of experience in data platform engineering, platform engineering, data science, analytics, or a related field.
Deep expertise in systems architecture with experience in stateless, fault-tolerant systems and familiarity with event-driven patterns and distributed paradigms.
A strong track record of designing and scaling data systems that solve real user and business problems.
Hands-on experience designing, implementing, and executing large-scale data projects.
Fluency with SQL, GitOps, DBT, BigQuery, Kafka, Postgres, and ELT Data Pipelines.
A builder's mindset with a willingness to question assumptions and challenge conventional wisdom.
Bonus Points For:
Experience with cloud platforms (preferably GCP, but AWS or Azure is great too!).
Familiarity with CI/CD pipelines and observability tools like DataDog, ArgoCD, CircleCI, and Atlantis.
Experience working with infrastructure as code tools like Terraform, Helm, and Kubernetes.
Knowledge of cost efficiency, security, and observability best practices in data platforms.
Experience with Fivetran, Hightouch, and GraphQL.
Knowledge of Docker and other containerization technologies.