Senior Data Engineer, Product

Block•San Francisco, CA

18d•$168,300 - $297,000•Remote

About The Position

The Senior Data Engineer will support the Product Data Engineering Team, which builds and maintains the curated data foundation for Block’s product lines: Cash App, Square, Afterpay, and Tidal. The team transforms raw event streams, transactional systems, and operational data into governed, tested, reliable analytical assets across domains such as banking, lending, commerce, investing, checkout, and AI assistants. It partners with Product, Engineering, Data Science, Machine Learning, and Applied AI teams to provide metrics, experimentation frameworks, and ML-ready datasets that support product growth and customer service at scale. The role covers data architecture and modeling, data pipeline tooling, and dashboarding. The engineer will create and optimize data models, own critical data pipelines, establish data quality and lineage monitoring, and develop AI-assisted automation. They will also work with technical and non-technical stakeholders to translate business needs into data requirements and automated end-to-end solutions.

Requirements

At least 10 years of related experience with a Bachelor’s degree, or 8 years with a Master’s degree, or equivalent experience.
High proficiency in SQL, Python, and dbt.
Experience designing medium-to-large data engineering solutions and owning their full lifecycle, including scoping, design, development, testing, deployment, and documentation.
Experience with ETL scheduling technologies that support dependency checking, such as Airflow or Prefect.
Experience in schema design and dimensional data modeling.
Experience setting up data quality and data lineage monitoring.
Experience using data-driven decisions through AI and agentic automation.

Responsibilities

Lead the creation and optimization of data models across eventing, customer-level, and process-level data, using AI-assisted development tools to accelerate delivery.
Take shared or independent technical ownership of critical data pipelines across Block, including foundational customer datasets, money transfer and movement pipelines, and infrastructure for the experimentation platform.
Build monitoring for data quality and lineage, and develop AI agents to reduce false positives and automate resolution.
Participate in an on-call rotation; monitor daily pipeline execution, diagnose and log issues, and fix business-critical pipelines to meet stakeholder SLAs.
Automate pipeline monitoring and issue resolution with AI agents to focus human effort on the highest-priority tasks.
Partner with non-technical stakeholders and product teams to understand needs, translate business requirements into data requirements, and develop automated end-to-end solutions.
Manage the full lifecycle of data engineering projects, including scoping, design, development, testing, deployment, and documentation.