Senior Data Engineer - 16615

Location: Remote, US work hours 

We are seeking a highly skilled Senior Data Engineer with strong experience in both data engineering and workflow automation. This role requires someone who can own end-to-end data systems, rapidly adapt to a new environment, and build reliable, scalable, and well-architected data pipelines with minimal oversight.

• Build, maintain, and optimize SQL- and Python-based data pipelines across extraction, linkage, enrichment, and modeling layers.

• Design autonomous, reliable ETL/ELT workflows capable of running with minimal intervention.

• Integrate pipelines with third-party APIs and external data sources.

• Apply deep SQL expertise, including performance tuning, query plan analysis, window functions, CTEs, and complex analytical query design.

• Optimize large-scale data warehouse environments for speed, reliability, and cost efficiency.

• Develop and manage workflows using modern orchestration frameworks (e.g., Airflow, Prefect, Dagster, dbt jobs, event-driven pipelines, or comparable tools).

• Implement automation for data processing, quality monitoring, environment promotion, and deployment workflows.

• Build resilient, testable, version-controlled data environments with CI/CD integration.

• Define and maintain schema design, data models, and performance diagnostics.

• Provide production support and continuously improve data systems through iteration.

• Work comfortably with financial, insurance, or regulatory datasets (preferred but not required).

• Operate as a senior individual contributor: self-directed, proactive, and capable of owning complex systems from design through ongoing operations.

• Extensive experience building SQL + Python data pipelines at scale.

• Deep SQL expertise, including advanced query design and warehouse optimization.

• Strong Python engineering background focused on data processing and automation.

• Hands-on experience with orchestration tools such as Airflow, Prefect, Dagster, dbt Cloud jobs, or similar systems.

• Experience implementing CI/CD, automated testing, monitoring, and version control in data environments.

• Ability to rapidly become productive in unfamiliar systems while working autonomously.

• Experience with financial, insurance, or regulatory data is a strong plus.