Data Engineer - Real-Time Identity Graph Pipelines

Baselayer; San Francisco, Northern (CA, KY); Hybrid; USD 120,000 - 150,000; Full time

Benefits offered by this job

Flexible PTO

SF office

Competitive pay

Equity

Career growth

Job summary

Baselayer is building the most comprehensive identity graph of US businesses, turning messy data into trustworthy signals. You’ll own end-to-end ETL pipelines, write production code, and collaborate with data scientists and ML engineers to feed models that power real-time entity resolution.

This is a hands-on, early-career friendly data engineer role based in San Francisco with a hybrid schedule. You’ll learn rapidly while shipping production-grade data infrastructure that scales across

Qualifications

• 1+ years of data engineering experience with Python, SQL, and cloud-native data platforms.
• Experience building and maintaining production ETL/ELT pipelines.
• Hands-on with modern data stack tools (Dataflow, Spark, Airflow or equivalents).

Responsibilities

• Build and maintain ETL/ELT pipelines ingesting and normalizing data from multiple sources.
• Develop data models and transformation layers powering fraud detection and KYB APIs.
• Implement data quality checks, observability tooling, and alerting to catch issues early.
• Tune pipelines and queries for performance, freshness, and cost in our cloud data warehouse.
• Collaborate with data scientists, ML engineers, and product teams to provide well-modeled data for entity resolution.
• Help ensure pipelines meet security and regulatory standards (SOC 2, GDPR, KYC/KYB).

Skills

Python

SQL

Cloud data platforms

ETL/ELT pipelines

Data modeling

Tools

Dataflow

Spark

Airflow

BigQuery

Snowflake

Job description

Baselayer is building the most comprehensive identity graph of US businesses, turning messy data into trustworthy signals. You’ll own end-to-end ETL pipelines, write production code, and collaborate with data scientists and ML engineers to feed models that power real-time entity resolution.

This is a hands-on, early-career friendly data engineer role based in San Francisco with a hybrid schedule. You’ll learn rapidly while shipping production-grade data infrastructure that scales across