[Hiring] Senior Data Engineer @Block

Role Description

As a Data Engineer, you will handle everything from data architecture and modeling to data pipeline tooling and dashboarding. You will enable a range of other engineering and business teams to make impactful business decisions by laying the foundation of our large and unique datasets that span across multiple products. This role will support the product data engineering team.

The Product Data Engineering Team at Block builds and maintains the curated data foundation that powers all of Block's product lines — Cash App, Square, Afterpay, and Tidal. We transform raw event streams, transactional systems, and operational data into governed, tested, and reliable analytical assets across domains including banking, lending, commerce, investing, checkout, and AI assistants. We partner with Product, Engineering, Data Science, Machine Learning, and Applied AI teams to deliver the metrics, experimentation frameworks, and ML-ready datasets that enable Block's products to grow, improve, and serve customers at scale.

You Will

• Lead the creation and optimization of data models across eventing, customer-level, and process-level data, leveraging 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 the data infrastructure powering Block's experimentation platform.
• Build monitoring to assess data quality and lineage and further, build AI agents for false positive reduction and automated resolution.
• Participate in on-call rotation, monitor daily execution, diagnose and log issues, and fix business critical pipelines to ensure SLAs are met with internal stakeholders. Automate this process through AI agents to focus human effort on highest priority tasks.
• Work with non-technical partners and product teams to understand their needs, translate business requirements into applicable data requirements, and develop automated end-to-end solutions.

Qualifications

• A minimum of 10 years of related experience with a Bachelor’s degree; or 8 years and a Master’s degree; or equivalent experience.
• High proficiency in SQL, Python, and Dbt.
• Experience designing medium-to-large data engineering solutions and responsible for the entire lifecycle of projects including scoping, design, development, testing, deployment, and documentation.
• Experience with ETL scheduling technologies with dependency checking, such as Airflow or Prefect.
• Experience in schema design and dimensional data modeling.
• Experience with setting up data quality and data lineage monitoring.
• Experience with data driven decisions through AI and agentic automation.

Technologies We Use and Teach

• Snowflake
• Databricks
• Dbt
• Github
• Airflow
• Prefect
• Omni
• Terraform

Benefits

• Remote work
• Medical insurance
• Flexible time off
• Retirement savings plans
• Modern family planning