Data Engineer

About Baselayer
Trusted by 2,200+ financial institutions, Baselayer is the intelligent business identity platform that helps verify any business, automate KYB, and monitor real-time risk. Baselayer’s B2B risk solutions and identity graph network leverage state and federal government filings and proprietary data sources to prevent fraud, accelerate onboarding, and lower credit losses.

About the Role
We are looking for a Data Engineer to build and scale Baselayer’s data infrastructure. You will own the pipelines and data systems that power analytics, reporting, and machine learning across the company, with a focus on reliability, performance, and data quality.

This role is hands-on and highly cross-functional. You will work closely with Product and Engineering to ensure data is accessible, trusted, and delivered in a way that supports product capabilities in a regulated environment.

What You’ll Do

• Design, build, and maintain scalable data pipelines that ingest, clean, validate, and transform data from internal systems and external sources
• Own data reliability and quality through monitoring, alerting, lineage, and validation frameworks
• Build and maintain data models and curated datasets that support analytics, dashboards, customer reporting, and downstream ML use cases
• Partner with Engineering to define best practices for data architecture, storage, access controls, and performance
• Implement orchestration and scheduling for batch and near-real-time workflows as needed
• Optimize pipeline performance, cost, and scalability as data volumes grow
• Develop and maintain documentation and runbooks for pipelines, datasets, and operational procedures
• Identify data gaps and instrumentation needs, and work with engineering teams to improve event capture and logging

About You
You want to learn fast, take ownership, and do work that matters. You are not just doing this for the win. You are doing it because you have something to prove and want to be great.

You thrive in the details, care about correctness, and take pride in building robust systems that other teams can rely on. You operate with urgency, handle ambiguity well, and consistently raise the bar on data quality and reliability.

Required Experience and Skills

• 1 to 3 years of experience in data engineering, analytics engineering, or backend engineering with significant data pipeline ownership
• Strong Python skills and experience building production-grade data workflows
• Strong SQL skills with experience designing data models and transforming large datasets
• Experience building and maintaining ETL or ELT pipelines and working with data warehouses or analytics databases
• Familiarity with orchestration tools and workflow scheduling (for example Airflow, Dagster, Prefect, or similar)
• Strong understanding of data quality, testing, observability, and operational best practices
• Comfort working with large-scale datasets and troubleshooting performance issues
• Ability to communicate clearly with technical and non-technical stakeholders

What Sets You Apart

• Experience working with identity, fraud, risk, compliance, or other regulated datasets
• Experience integrating with external data sources, APIs, and government or registry data
• Familiarity with streaming or near-real-time data patterns
• Highly feedback-oriented with a desire for continuous improvement

Work Location

• Hybrid in SF, in office 3 days per week

Compensation and Benefits

• Salary range of $122,000 to $167,000
• Equity package
• Unlimited vacation
• Comprehensive health coverage
• 401(k) with company match