Analytics Engineer

Pacific Life is an insurance company that collaborates and innovates to support policyholders and transform the insurance industry. The Analytics Engineer will transform enterprise data into trusted, reusable analytics products for reporting, machine learning, data science, and AI-powered business solutions while partnering with stakeholders and technical teams to develop scalable analytical models.

Responsibilities

Develop and maintain modular SQL transformations and analytical data models using dbt and Snowflake, creating reusable data sets for reporting, analysis, data science, and AI use cases

Partner with stakeholders to understand business processes and translate requirements into clear data definitions, business rules, metrics, and semantic models. Document relationships and assumptions so data can be interpreted consistently

Build automated tests, validate business logic, investigate discrepancies, and maintain documentation and lineage to help ensure analytical data is accurate, understandable, and reliable

Contribute to the development, testing, and evaluation of Snowflake Cortex solutions and AI agents grounded in trusted enterprise data and business context

Use Git, Azure DevOps (ADO), and CI/CD workflows to manage work, collaborate through pull requests, automate validation, and deliver controlled changes across development and production environments

Apply approved tools such as Claude Code and GitHub Copilot to development, testing, documentation, and workflow automation. Review and validate AI-generated outputs while following engineering, privacy, and security standards

Provide hands-on guidance, demonstrations, documentation, and knowledge transfer that help business partners adopt analytics products, use Snowflake Cortex, and become more self-sufficient

Troubleshoot analytical models and workflows, improve query performance and efficiency, modernize manual processes, and contribute reusable patterns and improvements to the team’s engineering playbook

Work with data engineering, platform, governance, and technology partners to deliver solutions that align with enterprise architecture, access controls, and operational standards, including AWS-based components where applicable

Preferred

professional AWS experience

Experience with Azure DevOps (ADO) or a comparable delivery platform

Experience with Snowflake Cortex, AI agents, or generative AI solutions

Familiarity with Claude Code, GitHub Copilot, or other AI-assisted and agentic development tools

Experience in insurance, financial services, or another regulated environment

Azure DevOps

Delivery Platforms

Snowflake Cortex

AI Agents

Generative AI Solutions

Claude Code

GitHub Copilot

AI-Assisted Development Tools

Agentic Development Tools

Insurance Industry Experience

Financial Services Experience

Regulated Environment Experience

Benefits

Medical, Dental, Vision, and Wellbeing Reimbursement Account for employees or their eligible dependents

Paid Time Off, Holiday Schedules, and Financial Planning Time Off

Paid Parental Leave

Adoption Assistance Program

401k savings plan with company match and an additional contribution regardless of participation

Company

Life insurance, annuities, and mutual funds provider

Newport Beach, California, USA

http://www.pacificlife.com/

Founded in 1868

1001-5000 employees

Qualifications

Bachelor's degree in Computer Science, Information Systems, Data Analytics, Mathematics, Engineering, or a related field, or equivalent practical experience

Typically at least 2–5 years of professional experience in analytics engineering, data engineering, business intelligence development, or a related technical role

Hands-on professional experience with dbt and Snowflake, including developing, testing, documenting, and maintaining analytical data models

Strong SQL skills and practical understanding of relational and dimensional modeling, data transformation, business logic, and query optimization

Experience with Git version control, branching, pull requests, code reviews, automated testing, and CI/CD

Working knowledge of Python for scripting, automation, or data-related development

Familiarity with AWS and cloud-based data environments

Ability to translate business questions into technical requirements, explain technical concepts clearly, and help stakeholders understand and use analytical solutions

A thoughtful, detail-oriented approach to troubleshooting, validating results, documenting decisions, and following work through delivery

Professional AWS experience

Experience with Azure DevOps (ADO) or a comparable delivery platform

Experience with Snowflake Cortex, AI agents, or generative AI solutions

Familiarity with Claude Code, GitHub Copilot, or other AI-assisted and agentic development tools

Experience in insurance, financial services, or another regulated environment

Typically at least 2–5 years of professional experience in analytics engineering, data engineering, business intelligence development, or a related technical role.

Required skills

dbt, Snowflake, SQL, Relational and Dimensional Data Modeling, Git, CI/CD, Python, AWS, Azure DevOps, Snowflake Cortex, Generative AI, Insurance

Preferred skills

professional AWS experience

Experience

2+ years