# Data Engineer

**Company:** [Baselayer](https://hotfix.jobs/companies/baselayer)
**Location:** San Francisco, CA
**Role:** Data Engineering
**Salary:** $120k – $150k/yr
**Experience:** 1+ years
**Skills:** Python, SQL, Dataflow, Spark, Apache Airflow, ETL, ELT, BigQuery, Snowflake, Kafka, GCP, Pub/Sub, Data Modeling, Data Quality, Cloud Run
**Posted:** 2026-09-03

> Build and operate production data pipelines and transformation layers that turn heterogeneous business, identity, and fraud data into reliable inputs for entity resolution, scoring, and customer APIs. The role requires at least one year of data engineering experience with Python, SQL, cloud platforms, and modern pipeline tooling.

## Job Description

## Responsibilities
- Build and maintain ETL/ELT pipelines ingesting and normalizing public records, web signals, and fraud telemetry.
- Develop data models and transformation layers using tools such as Dataflow, Spark, and Airflow to support fraud detection, KYB, and customer-facing APIs.
- Implement data quality checks, observability tooling, and alerting.
- Tune pipelines and queries for performance, freshness, and cost in the cloud data warehouse.
- Collaborate with data scientists, ML engineers, and product teams to provide well-modeled data for entity resolution and scoring.
- Help ensure pipelines meet security and regulatory standards for sensitive data, including SOC 2, GDPR, and KYC/KYB.
- Document systems and communicate with technical and non-technical stakeholders.

## Requirements
- 1+ years of experience in data engineering with Python, SQL, and cloud-native data platforms.
- Experience building and maintaining production ETL/ELT pipelines.
- Working knowledge of modern data-stack tooling such as Dataflow, Spark, or Airflow.
- Hands-on experience with cloud data warehouses or data lakes, such as BigQuery or Snowflake.
- Strong data-modeling fundamentals and focus on data integrity and reliability.
- Comfort working with structured and unstructured data.

## Nice-to-Haves
- Interest in AI/ML infrastructure.
- Experience with streaming or real-time data systems such as Kafka or Pub/Sub.
- Exposure to KYC/KYB, fraud, risk, or underwriting data.
- GCP experience, including BigQuery, Cloud Run, Dataflow, or Pub/Sub.
- Experience working in an early-stage environment.

## Compensation and Benefits
- $120,000–$150,000 salary plus equity.
- Flexible PTO.
- 100% employer-paid health, dental, and vision premiums.
- 401(k) with company match.
- HSA contributions on applicable plans.
- $250 monthly gym stipend.

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