The opportunity
Instacarts Data Infrastructure organization builds and operates the systems that power our company’s data ecosystem, including a modern open data lakehouse on Apache Iceberg, a multi-engine compute platform for stream and analytical workloads, and self-serve tooling that helps…
What you'll do
Translate Instacart’s data strategy (e.g., monetization, federated access,: real-time) into an actionable multi-year architecture roadmap; align with leadership while evolving the platform for scale, maturity, and cost efficiency.
Own the open lakehouse foundation: define and deliver unified table formats, storage governance, and a multi-engine compute portfolio (interactive, batch, streaming) that enables portability and prevents lock-in.
Drive real-time and streaming infrastructure for critical use cases (Ads,: Fraud, ML): set deployment patterns, SLAs, and operational practices that balance performance, availability, and spend.
Pioneer AI-native data infrastructure engineering by applying LLM/AI tools to: the platform lifecycle—accelerating development, automation, observability, and cost optimization—and partnering to embed AI-powered capabilities into the platform.
Elevate engineering excellence: lead architecture reviews, mentor senior/staff engineers, influence hiring, and clearly communicate complex trade-offs to both technical and executive audiences to ensure cross-org alignment.
+ years of software engineering experience building and operating data: infrastructure or distributed systems at production scale.
What they're looking for
- Experience designing platform-level governance controls and familiarity with: compliance frameworks (e.g., SOX, CPRA, GDPR).
- FinOps experience optimizing data platform spend, including managing: multi-million dollar infrastructure budgets and negotiating vendor contracts.
- Deep SQL proficiency and strong skills in Python or Scala for systems-level development.
- Experience with orchestration (e.g., Apache Airflow) and data transformation: pipelines (e.g., dbt) in large-scale production environments.
- Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering,: Electrical Engineering, or equivalent practical experience.
