Data Analytics Engineer

The Data Analytics Engineer will help strengthen the Actuarial department’s data, reporting, and analytics capabilities. In this onsite role in San Diego, CA, you will take ownership of an actuarial sandbox datamart and trusted analytical datasets while partnering with business and technical teams to deliver governed data solutions.

Key Responsibilities

• Own, maintain, and enhance the actuarial sandbox datamart, including data architecture, permissions, documentation, and integration of new data sources.
• Act as the Actuarial department’s primary liaison for enterprise data platform initiatives, supporting requirements gathering, testing, issue resolution, implementation, and adoption.
• Lead data stewardship activities such as data validation, reconciliation, QA/QC, auditing, root-cause analysis, and remediation of data integrity issues.
• Automate data pipelines, reporting workflows, and repeatable analytical processes using SQL, Python, R, Power BI, Databricks, or comparable tools.
• Perform business analytics to support underwriting, claims, finance, distribution, and product decisions.
• Partner with actuarial staff on predictive modeling, segmentation, KPI development, model monitoring, and implementation of analytical solutions.
• Translate business questions into data requirements, analytical approaches, and actionable recommendations for technical and non-technical audiences.
• Coordinate day-to-day efforts and knowledge transfer from the department’s data engineering contractor, including documentation of systems and processes.
• Establish scalable standards for data development, version control, testing, documentation, deployment, and ongoing maintenance.
• Manage multiple recurring and ad hoc priorities while communicating status, risks, dependencies, and recommended actions.
• Identify opportunities to improve data quality, reporting efficiency, analytical capability, and support for business decisions.
• Design, develop, and maintain curated analytical datasets, Power BI semantic models, dashboards, recurring reports, and monitoring tools used for operational, actuarial, and executive reporting.

Required Qualifications

• Bachelor’s degree in data science, computer science, statistics, mathematics, actuarial science, engineering, or a related quantitative field.
• 3–5 years of relevant experience in analytics engineering, data engineering, business intelligence, or advanced analytics.
• Property and casualty insurance or workers’ compensation experience is preferred.
• Advanced proficiency in SQL and working proficiency in Python or R.
• Experience building and maintaining automated data pipelines, analytical datasets, and reporting solutions.
• Experience with Power BI, semantic models, dashboard development, and business intelligence solutions.
• Demonstrated ability to lead analytics, reporting, automation, or data engineering projects.
• Understanding of data quality, reconciliation, testing, and documentation practices.
• Strong written and verbal communication skills with technical and non-technical audiences.
• Ability to collaborate across departments and translate business needs into scalable data and analytical solutions.
• Experience coordinating contractors, vendors, or technical workstreams is preferred.
• Experience with Databricks, cloud data platforms, or comparable data environments.

Technologies

• SQL
• Python
• R
• Power BI
• Databricks

Salary and Location

• Location: San Diego, CA (onsite)
• Salary: USD 117,000 - 139,000 per year
• Minimum Experience: 3 years

Benefits

• Base Salary Range: $117,000–$139,000 annually
• Health
• Dental
• Vision
• Life
• Disability
• Wellness
• Paid Time Off
• 401(k) and Profit-Sharing plans

Additional Information

• They do not accept any unsolicited resumes from external recruiting agencies or firms.
• Sponsorship is not offered for this role.