Data Engineer

Baselayer is an intelligent business identity platform trusted by over 2,200 financial institutions. They are seeking a Data Engineer to build and scale their data infrastructure, focusing on data pipelines that support analytics, reporting, and machine learning while ensuring data reliability and quality.

Responsibilities

• 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

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
• 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

Benefits

• Equity package
• Unlimited vacation
• Comprehensive health coverage
• 401(k) with company match

Company Overview