Senior Data Engineer, Underwriting Technical Lead

Responsibilities

• Develop and deploy sophisticated data pipelines and analytics solutions, troubleshoot issues, apply transformations, and advocate for data cleansing and quality improvements.
• Architect comprehensive data architectures, integrate new data sources, and ensure design consistency across initiatives aligned with the data strategy.
• Assess diverse data sources to determine value and applicability, recommending data for inclusion in analytics workflows.
• Embed core data management practices including governance, security, and data quality controls.
• Serve as a data and technology subject matter expert within business lines, supporting delivery and training end users on data products and the analytics environment.
• Conduct data and system analysis, diagnose defects and high complexity incidents, and implement appropriate resolutions.
• Collaborate with cross functional teams to enable delivery and educate end users on complex data products and analytics environment.
• Perform other duties as assigned.

Requirements

• Bachelor’s degree in a STEM field or equivalent.
• Ten years of related experience.
• Proven expertise designing, building, and sustaining scalable data pipelines on AWS, with hands on work across S3, Glue, Redshift, Lambda, and EMR.
• Strong Databricks experience, including developing and optimizing data workflows and leveraging Lakehouse architecture for large scale processing.
• Solid understanding of AI and ML concepts, with ability to collaborate with data science teams and support deployment or operation of models within the data ecosystem.
• Hands on experience with dbt for data modeling, transformation, and documentation, applying robust software engineering practices to analytics workflows.
• Advanced PySpark skills for distributed processing, capable of producing production grade code for large scale batch and streaming workloads.
• Candidates from Azure environments (Azure Data Factory, Synapse Analytics, Azure Databricks) will be considered if they demonstrate the ability to operate effectively within an AWS based stack.
• Willingness to assume a technical leadership role, mentoring engineers, guiding architectural decisions, and partnering with stakeholders across engineering and the business.
• Bachelor’s degree in computer science or related STEM field, or equivalent education/experience.
• 6 additional years of data engineering experience.

Technologies

• AWS ecosystem and services: S3, Glue, Redshift, Lambda, EMR
• Databricks and Lakehouse tooling
• dbt for modeling and documentation
• PySpark for distributed processing
• Azure Data Factory, Synapse Analytics, Azure Databricks

Benefits

• Health coverage
• Retirement savings plan
• Paid time off
• Wellness program
• Encouragement of volunteering

Employment Practices

Travelers is an equal opportunity employer. We value the unique abilities and talents each individual brings to our organization and recognize that we benefit in numerous ways from our differences.