We're transforming the grocery industry
At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.
Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.
Instacart is a Flex First team
There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.
Overview
Instacarts Data Governance & Foundations team builds and operates the core systems that power the company's data ecosystem — a modern data lakehouse at scale, spanning ingestion, stream processing, analytical compute, and self-serve tooling. You'll join a collaborative team of 6–7 engineers responsible for keeping a highly reliable production platform running today while architecting the infrastructure that will serve the business for the next 3–5 years.
This is a high-ownership, high-autonomy role. Architectural decisions carry both technical and financial weight, and you'll be expected to drive direction, not just execute it. You'll work closely with engineering leadership and cross-functional partners across Data Science, ML Platform, Ads Infrastructure, Finance Engineering, and senior stakeholders throughout the organization.
About the Job
- Define and drive multi-year architecture roadmaps for large-scale data ingestion and processing infrastructure, setting technical direction that balances reliability, scalability, and cost.
- Own end-to-end platform initiatives — from build vs. buy decisions and migration design through production rollout and risk management — across Kafka-based streaming and Postgres-based systems.
- Partner with vendors (Snowflake, Databricks, Confluent) on technical integration, contract evaluation, and TCO modeling to inform infrastructure investment decisions.
- Collaborate with various teams to embed governance and compliance controls (SOX, CPRA, GDPR) directly into platform architecture and data lifecycle management.
- Optimize infrastructure spend at scale: identify cost reduction opportunities across compute, storage, and pipeline efficiency; manage multi-million dollar infrastructure budgets.
- Write compelling architecture documents, strategy memos, and proposals that drive alignment with engineering leadership and senior stakeholders across the organization.
- Mentor engineers on the team, model strong engineering culture, and help grow a high-performing data infrastructure organization.
- Collaborate with Data Science, ML Platform, Ads Infrastructure, Finance Engineering, and Product teams to ensure the platform meets evolving needs.
About You
Minimum Qualifications
- 5+ years of software engineering focused on data infrastructure or distributed systems at scale, in a high-growth, data-intensive environment.
- Experience in modern data lakehouse architectures and open table formats — Apache Iceberg, Delta Lake, Hudi — with strong understanding of compute/storage trade-offs.
- Hands-on experience with distributed query and compute systems (Trino, Spark, ClickHouse) including performance tuning and production reliability work.
- Proven depth in event-driven infrastructure: Kafka for high-throughput data ingestion and Flink (or equivalent) for stream processing at scale.
- Track record owning and executing major platform transitions, including migration design, phased rollout, and risk management under production constraints.
- Experience building business cases for infrastructure investments: cost-benefit analysis, TCO modeling, and presenting recommendations to leadership.
- Exceptional written technical communication — clear architecture docs, strategy memos, and cross-team proposals that drive decisions and alignment.
- Strong ownership and comfort operating in ambiguity; ability to drive large, multi-team initiatives from concept to production with organizational influence.
Preferred Qualifications
- Familiarity with data governance and compliance frameworks (SOX, CPRA, GDPR) and experience designing governance controls into platform architecture.
- Experience with FinOps and data platform cost optimization, including managing large infrastructure budgets and negotiating enterprise vendor contracts.
- Deep SQL expertise and strong proficiency in Python or Scala for systems-level work.
- Experience with orchestration (Apache Airflow) and transformation pipelines (dbt) in large-scale production environments.
- Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
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