Senior Data Engineer - Remote, AI-Driven Data Pipelines

Unchain Data; Los Angeles (CA); Remote; USD 168,000 - 297,000; Full time

Benefits offered by this job

Remote work

Medical insurance

Flexible time off

Retirement savings plans

Family planning support

Job summary

Block is seeking a senior Data Engineer to shape the data architecture and pipelines powering Cash App, Square, Afterpay, and Tidal. You will enable cross-functional teams by building scalable, governed datasets and analytics assets across banking, lending, commerce, investing, and AI workloads.

You will collaborate with Product, Engineering, Data Science, and ML teams to deliver metrics, experimentation frameworks, and ML-ready datasets.

Qualifications

• 10+ years of related experience with data engineering focus.
• Strong proficiency in SQL, Python, and Dbt.
• Experience designing medium-to-large data pipelines and lifecycle delivery.
• Experience with Airflow or Prefect ETL scheduling.
• Data modeling and dimensional design experience.
• Experience with data quality and data lineage monitoring.
• Experience with AI-assisted automation and agentic automation.

Responsibilities

• Lead creation and optimization of data models across eventing and customer-level data.
• Own critical data pipelines and data infrastructure powering experimentation.
• Build monitoring for data quality and lineage; develop AI agents for automated resolution.
• Participate in on-call rotation; diagnose and fix pipelines to meet SLAs.
• Translate business needs into automated end-to-end data solutions with non-technical partners.

Skills

SQL

Python

Dbt

Data engineering design

Data quality monitoring

AI automation

Education

Bachelor's degree or higher

Tools

Snowflake

Databricks

Dbt

Github

Airflow

Prefect

Omni

Terraform

Job description

Block is seeking a senior Data Engineer to shape the data architecture and pipelines powering Cash App, Square, Afterpay, and Tidal. You will enable cross-functional teams by building scalable, governed datasets and analytics assets across banking, lending, commerce, investing, and AI workloads.

You will collaborate with Product, Engineering, Data Science, and ML teams to deliver metrics, experimentation frameworks, and ML-ready datasets.