Senior Data Engineer

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About Mission Underwriting Services:
At Mission Underwriters, we provide the capital, issuing paper, and reinsurance access you need to launch your own Program Administrator (PA) business quickly and efficiently. We offer non-recourse capital for qualified underwriters, giving you a manageable risk profile with potential equity upside. By taking care of administrative complexities like compliance, risk management, accounting, and HR, we free you to focus on what you do best—underwriting and distribution.

Our turnkey platform gets you into the market in just a few months, minimizing disruption to your key relationships. With access to our network of issuing carriers and reinsurance partners, you can secure coverage with less stress and uncertainty. Built from the ground up, our technology simplifies workflows, enhances responsiveness, and eliminates the burden of outdated legacy systems.

What We Offer

• Remote First Work Environment (US Based)
• Medical, Dental, Vision
• 401K, 401K Match
• Life and Disability Benefits
• Unaccrued Paid Time Off
• 11 Paid Holidays
• Employee Discounts
• Employee Assistance Program
• Educational Assistance Program
• Employee Referral Program
• Paid Parental Leave
• Previous Insurance Experience Is Required For This Role

About The Role

The Senior Data Engineer will play a key role in designing, implementing, and optimizing Mission’s data infrastructure as part of our modern data platform initiative. This hands-on engineering role will focus on building scalable data pipelines, enabling a centralized enterprise data warehouse, and supporting business reporting needs. The ideal candidate will collaborate across technology, operations, product, and analytics teams to create high-quality, governed, and reusable data assets, while supporting a long-term architecture aligned with Mission’s growth.

This role is highly technical and focused on execution and is ideal for a data engineer who thrives in fast-paced environments and is passionate about data quality, performance, and scalability.

What You'll Do

• Design and implement scalable data pipelines to ingest, transform, and store data from third-party vendors and internal systems using APIs, files, and databases.
• Build and maintain a cloud-based data warehouse solution in partnership with architects, ensuring clean, normalized, and performant data models.
• Establish and monitor reliable data ingestion processes across systems with varying grain and cadence, ensuring data quality and completeness.
• Collaborate with API and integration teams to develop secure, robust data exchange processes with external vendors and internal services.
• Set up and manage data connections from the warehouse to BI tools (Power BI, Looker, Tableau) to enable self-service analytics and dashboarding.
• Document data flows, schemas, and definitions, and help drive data governance and standardization efforts across the organization.
• Implement data validation, cleansing, and enrichment processes to ensure high-quality data for financial reporting and analytics.
• Ensure compliance with data standards, regulatory requirements (e.g., NAIC, SOX), and data security best practices.
• Provide technical leadership in data engineering best practices, including version control, CI/CD for data pipelines, testing, and observability.
• Build initial dashboards in BI tools.
• Provide direction to data engineers to ensure that projects are completed on time and to a high standard.

Required Qualifications

• 5+ years of experience in data engineering, data warehousing, or a related field with at least 1-2 years leading implementation projects.
• 3+ years of experience in the commercial insurance industry.
• Hands on experience with Azure data services.
• Strong SQL and performance tuning skills in Microsoft SQL Server environments.
• Experience designing data warehouses or data marts with a focus on dimensional modeling and analytics-ready schemas.
• Fluent in range of data ingestion: RESTful APIs, JSON/XML ingestion, flat files, message queues, and CDC patterns.
• Understanding of data governance, metadata management, and access control.
• Familiarity with version control (Git Lab) and CI/CD pipelines for data workflows.
• Experience working with BI tools like Power BI, Looker, or Tableau, including building dashboards or semantic layers.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent experience.
• Demonstrated ability to translate business needs into scalable data systems and design.

Preferred Qualification

• Experience with data cleanup, fuzzy matching, or AI-driven normalization.
• Familiarity with Python, dbt, or Azure Functions is a plus.
• Strong communication skills and ability to work cross-functionally with product, engineering, and analytics teams.
• Ability to travel up to 10% of the year.

Knowledge,

Skills And Abilities

• Deep understanding of data warehousing principles, dimensional modeling, and ETL/ELT architecture, with hands-on experience building analytics-ready…