Senior Data Engineer

Description

The Data Engineering team builds the pipelines, models, and data services behind reporting, analytics, and data science for the company's lending and insurance businesses.

The work includes hard integration and modeling problems, improving reliability and cost efficiency, and using practical AI tools to deliver data solutions sooner.

You will work with your manager, fellow engineers, and partners in analytics, data science, product, and business operations, and with platform and infrastructure teams on dependencies and production services.

Strong candidates are curious about the business behind the data, learn new tools with care, raise issues early, and share credit and lessons learned.

Success means production pipelines meet agreed freshness and reliability targets, partners work from tested models with consistent definitions, and reusable frameworks and validated AI workflows shorten delivery time.

Responsibilities

• Build and run scalable batch and real-time streaming pipelines, ETL/ELT workflows, and database applications across several lines of business, with planned approaches for schema changes, retries, and recovery.
• Design dimensional models and reusable datasets for business, analytics, and data science use, and run complex analysis to check business rules and surface trends, anomalies, and opportunities.
• Keep your data solutions reliable and efficient: automate quality checks, watch data freshness, tune performance and compute spend, and take a turn on the on-call rotation to resolve incidents and prevent repeats.
• Build reusable frameworks and development patterns that speed up and standardize delivery, using automated testing, code review, and repeatable deployments, and keep standards, runbooks, and training material current.
• Work with business users and engineering teams to pin down requirements and resolve issues, and help shape the data engineering roadmap, including platform features, priorities, trade-offs, and estimates.
• Use AI tools for coding, testing, documentation, and troubleshooting, check generated code and output, protect sensitive data, and judge whether the tools improve quality and cut delivery time.

Requirements

• 5+ years of hands-on data engineering work covering data warehousing, ETL/ELT development, and analytics, with production solutions you have delivered and supported.
• Advanced SQL skills: write, tune, and debug complex queries, and use data analysis to investigate problems.
• Experience designing data lakes and warehouses on scalable distributed platforms, and an understanding of batch and streaming integration patterns.
• Strong dimensional modeling and sound warehousing practice, including setting grain, defining fact and dimension tables, and recording how historical changes are represented.
• Deliver projects with little guidance in an Agile team, using testing, version control, documentation, and methodical troubleshooting to build solutions that are easy to maintain.
• Communicate clearly in writing, speech, and data presentations, understand business needs, and explain findings and technical decisions through documents, presentations, or dashboards.
• Plus: Snowflake virtual warehouses, performance and cost tuning, Streams and Tasks, or SQL Server experience.
• Plus: Matillion, dbt, or similar data integration and transformation tools.
• Plus: Python, C, or PowerShell for integration and automation, and Git/GitLab for collaboration and CI/CD workflows.
• Plus: Power BI, Tableau, or Streamlit for dashboards, data applications, and sharing insights.
• Plus: Hands-on use of AI-assisted development tools such as Claude Code, Codex, Cursor, or Maia, with validation of generated code and results.
• Plus: An S. degree in Computer Science, Mathematics, or a related field, or equivalent practical experience.

Conditions

Candidates must be legally authorized to work in the United States. The company will not provide or assume employment visa sponsorship for this role, now or in the future.

Base pay is $100,000-130,000, and the offer may vary by location, internal factors, job-related knowledge, skills, and experience.

The company is an equal opportunity employer and does not discriminate on grounds including race, religion, gender, age, disability, and military status.

Benefits

• Medical, dental, and vision insurance.
• 401(k) with company matching.
• Generous time off.
• Wellness programs and resources.
• Eligibility for an annual performance bonus.