Senior Staff Software Engineer, Instacart

• This is a role for a systems thinker who thrives at the intersection of deep technical depth and company-level strategic impact
• 10+ years of software engineering, focused on data infrastructure or distributed systems at scale.Sets technical direction for large-scale data platforms, defining multi-year architecture roadmaps and influencing strategy. Experience in high-growth, data-intensive environments with significant infrastructure scale and spend
• Expertise in modern data lakehouse architectures, open table formats (Iceberg, Delta Lake, Hudi), and compute/storage trade-offs, in distributed query/compute systems (Trino, Spark, ClickHouse, etc.) for performance tuning and production reliability and event-driven infrastructure (Kafka, Flink, etc.)
• Proven track record owning and executing major infrastructure platform transitions, including build vs. buy, migration design, and risk management
• Experience building compelling business cases for infrastructure investments, including cost-benefit analysis and TCO modeling
• Exceptional technical communication for clear architecture documents, strategy memos, and proposals to drive leadership alignment. Strong ownership, comfort with ambiguity, and organizational influence to drive large, multi-team initiatives from concept to production

Desirable

• Instacart's backend systems serve millions of customers every year, processing petabytes of data daily to power everything from personalized grocery recommendations to real-time fraud detection and advertiser measurement
• As Senior Staff Software Engineer on the Data Infrastructure team, you will set the technical direction for the data platform that underpins the entire company’s data strategy — from the storage and compute layer to streaming infrastructure, analytics tooling, and governance systems
• You will define the multi-year architecture roadmap for our core data platform, drive major platform investment decisions, and operate as a thought leader both internally across engineering leadership and externally within the data infrastructure community
• Your work will directly influence how Instacart makes decisions at scale and shape the platform economics of one of the most data-intensive technology companies in grocery commerce
• The Data Infrastructure team builds and operates the systems that power Instacart’s data ecosystem — a modern data lakehouse built on Apache Iceberg, a multi-engine compute platform spanning stream processing and analytical query engines, and self-serve tooling that enables Product, Data Science, ML, Ads, Finance, and other engineering teams to move fast with data
• We balance two mandates: maintaining a highly reliable production data platform serving the business today, and architecting the infrastructure that will serve it for the next three to five years
• We operate in a world of significant scale and material infrastructure spend, where architectural decisions carry both technical and financial consequences
• Some of the core technologies in our stack include:
• Apache Iceberg, Apache Flink, Trino, ClickHouse, Apache Kafka, Apache Spark, Snowflake, Databricks, Confluent, Airflow, dbt, Delta Lake, Scala, Python, Postgres, and AWS
• The team operates with a high degree of ownership and autonomy
• You will work closely with engineering leadership, data science, ML platform, ads infrastructure, finance engineering, and senior stakeholders across the organization
• Define and Drive Data Infrastructure Vision: Own the multi-year technical vision and roadmap for Instacart’s core data platform (storage, compute, streaming, orchestration, analytical serving). Translate company data strategy (monetization, federated access, real-time) into a coherent, actionable architecture plan. Align with leadership and proactively evolve the architecture for scale, maturity, and cost
• Lead Platform Strategy (Build, Buy, Ownership): Architect the ownership strategy for the data platform, determining build vs. buy (including managed services vs. open-source self-hosting). Lead technical/business case evaluations, full cost-benefit modeling, and risk analysis for major investments. Design phased migrations to ensure reliability while achieving long-term independence and cost efficiency
• Own the Data Lakehouse Foundation: Drive the architecture and delivery of the open lakehouse, including unified table format, compute engine portfolio, and storage governance. Expand multi-engine compute (interactive, batch, stream processing). Define standards for data storage, access, governance, and sharing to enable compute portability and prevent lock-in. Ensure reliable scaling without proportional cost increase
• Drive Real-Time and Streaming Infrastructure: Own the architecture for streaming data, event-driven pipelines, stream processing, and real-time serving for critical use cases (Ads, Fraud, ML). Make principled decisions on deployment models balancing cost, availability, and operational maturity
• Pioneer AI-native Data Infrastructure Engineering: Lead the adoption, application, and cultural integration of AI/LLM tools across the data platform lifecycle, setting a high standard for AI-augmented workflows, driving high-leverage opportunities from automation to cost optimization, and partnering with other teams to embed AI-powered capabilities into the platform itself
• Elevate Engineering Excellence: Serve as the senior technical voice, setting standards for system design and reliability. Lead architecture reviews. Mentor staff/senior engineers, fostering ownership and execution. Be a visible engineering leader, contributing to hiring and cross-org alignment
• Partner Deeply with Stakeholders: Collaborate with Data Science, ML Platform, Ads Infra, Product Eng, Finance Eng, and Security to translate needs into reliable, self-serve infrastructure. Represent Data Infra in architectural forums, ensuring decisions support business priorities (monetization, compliance, AI). Clearly communicate complex trade-offs to technical and executive audiences