Data Engineering Manager, Core Experience & Incentives

Instacart is transforming the grocery industry by providing essential services that customers rely on for grocery delivery. The Data Engineering Manager will lead two high-impact teams to scale a centralized data engineering model, ensuring the delivery of reliable and trustworthy data across the organization.

Responsibilities:

• Own the vision, strategy, and roadmap for Core DE and CoreX/Incentives DE to deliver high-quality batch and streaming pipelines, trusted datasets, and scalable data models for mission-critical product and analytics use cases
• Lead, coach, and develop a team of 7 data engineers, creating growth opportunities, establishing clear goals and accountability, and hiring to scale as needs evolve
• Define and enforce engineering excellence standards for data modeling, testing, data quality, documentation, observability, SLAs, and cost/performance optimization
• Partner with DSA, ML, Product, and SWE to establish clear data contracts and deliver well-documented, versioned, and discoverable datasets that power experimentation, incentives, and marketplace operations
• Drive the centralization of data engineering by creating and iterating on intake and engagement models, migrating pipelines from product teams where appropriate, and measuring impact through clear OKRs
• Ensure strong governance and reliability through incident response, root cause analysis, prevention plans, and adherence to privacy, security, and compliance standards
• Communicate status, risks, and tradeoffs with clarity and candor to stakeholders and leadership, fostering alignment and predictable delivery

Requirements:

• 8+ years of experience in data engineering building and operating production-grade data pipelines and platforms
• 2+ years of experience directly managing data engineering teams with full people leadership responsibilities (hiring, performance, and career development)
• Proficiency in SQL and at least one programming language used for data engineering (Python or Scala)
• Hands-on experience with distributed processing and streaming technologies (e.g., Spark, Kafka, or Flink)
• Experience with modern cloud data warehouses and lakehouse architectures (e.g., BigQuery, Snowflake, Databricks, or Redshift)
• Experience orchestrating pipelines with tools such as Airflow, Dagster, or similar
• Strong background in data modeling (dimensional and normalized), data quality frameworks, and automated testing
• Proven success partnering cross-functionally with Product, Data Science, and Software Engineering to deliver end-to-end data solutions against clear SLAs/OKRs
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience
• Experience in e-commerce, marketplace, or consumer-scale technology environments
• Domain experience with incentives, promotions, pricing, growth, or experimentation data products
• Track record building central/platform data engineering capabilities and defining clear intake and engagement models with product teams
• Experience with data governance, lineage, and quality tooling (e.g., dbt, Great Expectations, Monte Carlo, DataHub, Amundsen, or similar)
• Demonstrated ability to optimize data systems for cost, performance, and reliability at scale
• Experience leading distributed or remote teams and establishing effective communication and execution rhythms
• Familiarity with ML feature engineering and partnering with ML teams (e.g., feature stores, real-time features)
• Advanced degree in a relevant field