Senior Data Engineer, Risk

Block•Bay Area, CA, United States of America, CA

3d•$168,300 - $297,000•Remote

About The Position

As a Data Engineer you will handle everything from data architecture and modeling to data pipeline tooling and dashboarding. You will enable other compliance and risk 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 compliance or risk product data engineering teams. The Compliance Data Engineering team at Block supports the detection and reporting of suspicious financial crimes activity across Cash App, Square, and Afterpay. We work globally with partners in business, engineering, counsel, and product to provide a safe user experience for our customers while minimizing and potentially eliminating bad activity on our platform. The Risk Product Data Engineering team at Block builds reliable data foundations that help protect customers across Cash App, Square, and Afterpay. We partner with product, engineering, compliance, and legal teams to support risk detection, reporting, instrumentation, and ML-ready datasets across critical domains including identity, account access, eligibility, controls, and disputes.

Requirements

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, as well as
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

Nice To Haves

Snowflake
Databricks
Dbt
Github
Airflow
Prefect
Omni
Terraform

Responsibilities

Lead the creation and optimization of existing data models through AI code generation on eventing, customer level, and process level data.
Standardize business and product metric definitions in curated and optimized datasets, and develop data dictionaries and other related documentation.
Build monitoring to assess data quality and lineage and on top 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 come up with automated end-to-end solutions.