Data Analytics Engineer

The Data Analytics Engineer will help strengthen the Actuarial department’s data, reporting, and analytical infrastructure by managing an actuarial sandbox datamart and trusted analytical datasets. In this onsite role in San Diego, CA, you will partner with business and technical teams to deliver governed data solutions and support analytics that inform underwriting, claims, finance, distribution, and product decisions.

Key Responsibilities

• Own, maintain, and enhance the actuarial sandbox datamart, including data architecture, permissions, documentation, and integration of new data sources.
• Act as the primary liaison for enterprise data platform initiatives, managing requirements gathering, testing, issue resolution, implementation, and adoption.
• Lead data stewardship activities such as validation, reconciliation, QA/QC, auditing, root-cause analysis, and remediation of data integrity issues.
• Automate data pipelines and reporting workflows, supporting repeatable analytical processes using SQL, Python, R, Power BI, Databricks, or comparable tools.
• Deliver business analytics supporting underwriting, claims, finance, distribution, and product decision-making.
• Partner with actuarial staff on predictive modeling, segmentation, KPI development, model monitoring, and the implementation of analytical solutions.
• Translate business questions into clear data requirements, analytical approaches, and recommendations for both technical and non-technical audiences.
• Coordinate day-to-day work 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 decision support.
• Design, develop, and maintain curated analytical datasets, Power BI semantic models, dashboards, recurring reports, and monitoring tools 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.
• 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

Compensation and Benefits

Base Salary Range: $117,000–$139,000 per year.

• Health
• Dental
• Vision
• Life
• Disability
• Wellness
• Paid Time Off
• 401(k) and Profit-Sharing plans

Location and Work Setting

San Diego, CA (onsite)

Additional Information

• We do not accept unsolicited resumes from external recruiting agencies or firms.
• Sponsorship Details: Sponsorship not offered for this role.