Sr. Data Engineer

Palomar•Edina, MN

3d•Onsite

About The Position

As a Senior Data Engineer at Palomar, you will lead the design, development, and optimization of robust, scalable data solutions that power our business. You will mentor junior engineers, drive best practices, and collaborate with cross-functional teams to deliver high-quality, production-ready data assets and pipelines. Your expertise will help shape our data architecture and ensure the reliability, security, and performance of our data ecosystem. For this role specifically, that work is centered on building and maintaining the data infrastructure for statistical reporting across all direct admitted business, in partnership with Actuarial and Compliance.

Requirements

6+ years of experience in data engineering or a related field, with a proven track record of delivering large-scale data solutions.
Advanced proficiency in SQL, Python (or similar), and experience with modern data warehousing (e.g., Snowflake, Redshift, BigQuery).
Deep understanding of data modeling, data architecture, and cloud platforms (AWS, Azure, GCP).
Experience with orchestration tools (e.g., Airflow, dbt, Cloud Composer).
Strong problem-solving, analytical, and communication skills.
Demonstrated ability to mentor and lead technical teams.
Insurance experience required.
Statistical reporting experience strongly preferred.

Nice To Haves

Build strong relationships through transparency, trust, and respect for each other.
Work in an agile environment, with a resilient mindset to find creative solutions to challenges.
Collaborate and celebrate diverse perspectives, promoting inclusivity and equality.
Do the right thing with strong conviction and integrity.
Be bold and innovative to help make an impact.
Demonstrable track record of working autonomously and driving progress
Be intellectually curious, think creatively, and pragmatic

Responsibilities

Lead Data Pipeline Development: Architect, build, and optimize complex ELT/ETL pipelines to ingest, transform, and deliver data from diverse sources at scale.
Data Architecture & Modeling: Design and implement advanced data models and architectures to support analytics, reporting, and operational needs.
Statistical Reporting: Partner with Actuarial and Compliance SMEs to build and validate source mappings + transformation logic; design system to generate filing-ready outputs for statistical agents.
Performance & Reliability: Proactively monitor, troubleshoot, and enhance data systems for performance, scalability, and reliability.
Data Quality & Governance: Champion data quality, integrity, and governance by implementing robust validation, monitoring, and compliance processes.
Collaboration & Leadership: Partner with business stakeholders, BI engineers, and database engineers to translate business requirements into technical solutions. Mentor and guide junior team members.
Documentation & Standards: Establish and maintain comprehensive documentation and promote engineering best practices across the team.
Innovation: Evaluate and introduce new technologies, tools, and methodologies to improve data engineering capabilities.