Senior Data Engineer - Snowflake T500-22882

Position: Senior Data Engineer - Snowflake [T500-22882]
About Arch:

Arch Capital Group Ltd. (Arch) is a leading global insurer with operations in more than a dozen countries. We write insurance, reinsurance and mortgage insurance on a worldwide basis, and our customers value us as an innovative partner and dependable risk manager with decades of fresh ideas and solid results. Part of the S&P 500, Arch has the size and capital position to remain a market-leading specialty insurer.

Sr Data Engineer

Job Description:

The Data Engineer will play a key role in designing, developing, and maintaining enterprise-grade ELT/ETL solutions within a Snowflake-based data warehouse environment. This individual will collaborate with internal and external partners across technology and business teams to deliver high-quality data products, enhance platform capabilities, and ensure the reliability of production data pipelines. The ideal candidate will possess strong SQL expertise, hands-on Snowflake and Informatica experience, and a solid background in ETL/ELT development using modern data engineering tools and practices.

This role requires the ability to critically analyze business requirements, design scalable data architectures, drive data quality and standardization initiatives, and mentor junior team members. Experience in the P&C insurance or reinsurance industry is highly desirable.

Responsibilities:

- Design, develop, and maintain ELT/ETL solutions within Snowflake and related cloud ecosystems.
- Produce detailed design specifications, technical documentation, and unit test plans.
- Critically analyze business requirements and translate them into robust, scalable data solutions.
- Architect and implement data models for data warehouse, data lake, and data hub environments.
- Develop and maintain data engineering standards, coding practices, and reusable frameworks.
- Work closely with product managers to identify gaps and develop actionable remediation plans.
- Partner with business stakeholders and technology teams to implement product and data enhancements.
- Recommend innovative solutions to improve performance, efficiency, and competitive positioning.
- Provide production maintenance and support for data pipelines and data warehouse environments.
- Build automated monitoring and alerting mechanisms for data loads and data quality checks.
- Ensure high system availability, reliability, and timely issue resolution.
- Contribute to the development and continuous improvement of data engineering best practices.
- Support data standardization, conformance, and transformation initiatives across the enterprise.
- Apply strong understanding of MDM and reference data to improve data consistency and usability.
- Adhere to CI/CD processes, source code management practices, and branching strategies (Git).
- Mentor and guide junior offshore developers to ensure delivery excellence. Confidential Information
- Foster a culture of quality, innovation, and continuous improvement

Required Qualifications:

- Strong proficiency in SQL, ELT/ETL design, and data transformation.
- Minimum 6-8 years of ETL/ELT experience using tools such as Informatica, Databricks, Snowflake, and Azure Data Factory.
- Minimum 3+ years of data engineering experience working with enterprise data pipelines.
- At least 2 years of hands-on Snowflake experience.
- Experience integrating external data feeds and enriching internal datasets.
- Strong understanding of data modeling methodologies (warehouse, lake, hub).

- Experience with automated pipeline monitoring and production support.
- Strong understanding of CI/CD tooling and pipelines in a data engineering context.
- Solid knowledge of Git, including branching, merging, conflict resolution, and baseless merges.
- Exposure to MDM and reference data management principles.
- Experience working in the insurance or reinsurance industry (highly desirable).
- 3+ years working in Agile/Scrum environments.
- Excellent communication skills and ability to collaborate with both technical and non-technical teams.
- Strong analytical thinking and problem-solving capabilities.
- Ability to recommend innovative ideas and drive continuous improvements.