Finance Technology Data Engineer III

Company Overview

More than 35 years ago, Select Quote was founded on one core promise:
to help our customers protect the people they value most. We pioneered the way consumers shopped for term life insurance, and now, we also help people find home insurance, auto insurance, senior health insurance and more. Our quick and easy process saves consumers both time and money, and today, more than 2 million families trust us to help them with their insurance needs.

The Fintech Data Engineer III role at Select Quote is responsible for the design development and maintenance of intricate reporting processes within a SQL Server environment specifically catering to the financial and accounting teams' needs. This position involves translating business requirements into technical specifications, implementing data snapshot strategies and data lockdown procedures, and performing in-depth auditing and validation of large financial datasets using SQL and Excel.

The Fintech Data Engineer III will also maintain and improve existing ETL solutions, collaborate to consolidate the data landscape, and mentor less experienced team members. The ideal candidate possesses strong SQL Server expertise, a solid understanding of data warehousing and ETL processes, excellent analytical and problem‑solving skills, and the ability to communicate complex technical concepts effectively.

This position has no direct supervisory responsibilities.

• Proven expertise in designing, building and maintaining intricate reporting processes within a SQL Server environment.
• Ability to translate business reporting requirements from finance and accounting teams into technical specifications and working solutions.
• Experience in designing and implementing data snapshot strategies to capture point‑in‑time financial data for reporting and auditing. Knowledge of data lockdown procedures to ensure data integrity and prevent unauthorized modifications during critical closing periods.
• Demonstrable experience in auditing and validating large complex financial datasets using SQL for data extraction, manipulation and comparison. Proficiency in utilizing Microsoft Excel for advanced data analysis, reconciliation and presentation of audit findings. Ability to identify data anomalies, discrepancies and inconsistencies and implement corrective actions.
• Maintain existing ETL solutions while looking for opportunities to improve them.
• Collaborate with other team members to consolidate the data landscape to reduce the development time and increase consistency among ETL solutions.
• Train and coach less experienced staff members in best practices.

• Excellent analytical and problem‑solving abilities. Strong attention to detail and commitment to data accuracy.
• Effective communication skills with the ability to explain complex technical concepts to non‑technical stakeholders in finance and accounting.
• Ability to work independently and as part of a collaborative team.
• Advanced proficiency in SQL Server (including T‑SQL stored procedures, views, functions).
  
  Experience with other database technologies (e.g. Postgre
  
  SQL, Oracle, SSAS) is a plus.
• Strong understanding of data warehousing concepts, ETL (Extract Transform Load) processes and data modeling techniques.
• Comfortable working with source control (bitbucket, git, Git Hub).
• Experience working in an agile environment.
• Objectivity and openness to others' views, providing solutions and creative input.
• Self‑motivated and excited to work with different technologies.
• Understanding of ETL concepts and ability to apply those concepts to multiple technologies.

• Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience).
• 6+ years of experience working within Data systems or equivalent training.
• 2+ years working with Financial/Accounting data/systems.
• 4+ years of strong experience troubleshooting stored procedures and other T‑SQL code.
• 2+ years of experience with Air Flow or equivalent training.
• 2+ years of experience in Python coding using advanced modules (Pandas, Numpy and other libraries).
• Microsoft SQL…