Senior Data Engineer

Mission US

140d•Remote

About The Position

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.

Requirements

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 (GitLab) 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.

Nice To Haves

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.

Responsibilities

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 (e.g., 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.
Give directions to data engineers to ensure that projects are completed on time and to a high standard.