Analytics Engineer

Job Description: Providing for loved ones, planning rewarding retirements, saving enough for whatever lies ahead – our policyholders count on us to be there when it matters most. It’s a big ask, but it’s one that we have the power to deliver when we work together. We collaborate and innovate – pushing one another to transform not just Pacific Life, but the entire industry for the better. Why? Because it’s the right thing to do. Pacific Life is more than a job; it’s a career with purpose. It’s a career where you have the support, balance, and resources to make a positive impact on the future – including your own. We’re actively seeking a talented Analytics Engineer to join our Analytics Engineering team as part of our Advanced Analytics function in our Newport Beach, CA office. Reporting to the Director, Analytics Engineering, this role will help transform enterprise data into trusted, reusable analytics products that support reporting, machine learning, data science, and AI-powered business solutions. You’ll collaborate with business stakeholders, analytics delivery, data engineers, visualization engineers, and data scientists to translate business needs into tested, documented, and scalable analytical models. Our work goes beyond building data transformations. We capture the business definitions, rules, and relationships that make data meaningful and usable by both people and AI agents. Working with dbt, Snowflake, Snowflake Cortex, AWS, and modern engineering practices, you’ll help deliver reliable analytics solutions while enabling stakeholders to confidently use data and AI. You’ll also contribute to our adoption of AI-assisted and agentic development using tools such as Claude Code and GitHub Copilot, with appropriate testing, human review, and security controls. How you will help move us forward · Analytics Engineering: 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. · Business Context and Semantic Modeling: 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. · Data Quality and Trust: Build automated tests, validate business logic, investigate discrepancies, and maintain documentation and lineage to help ensure analytical data is accurate, understandable, and reliable. · AI and Agentic Solutions: Contribute to the development, testing, and evaluation of Snowflake Cortex solutions and AI agents grounded in trusted enterprise data and business context. · Modern Development Practices: 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. · AI-Assisted and Agentic Development: 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. · Stakeholder Enablement: Provide hands-on guidance, demonstrations, documentation, and knowledge transfer that help business partners adopt analytics products, use Snowflake Cortex, and become more self-sufficient. · Reliability and Continuous Improvement: 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. · Cross-Functional Collaboration: 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. The experience you bring · Education: Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Mathematics, Engineering, or a related field, or equivalent practical experience. · Professional Experience: Typically at least 2–5 years of professional experience in analytics engineering, data engineering, business intelligence development, or a related technical role. · Core Stack Experience: Hands-on professional experience with dbt and Snowflake, including developing, testing, documenting, and maintaining analytical data models. · SQL and Data Modeling: Strong SQL skills and practical understanding of relational and dimensional modeling, data transformation, business logic, and query optimization. · Software Engineering Practices: Experience with Git version control, branching, pull requests, code reviews, automated testing, and CI/CD. Experience with Azure DevOps (ADO) or a comparable delivery platform. · Programming and Cloud: Working knowledge of Python for scripting, automation, or data-related development. Familiarity with AWS and cloud-based data environments; professional AWS experience is preferred. · Business Partnership: Ability to translate business questions into technical requirements, explain technical concepts clearly, and help stakeholders understand and use analytical solutions. · Problem Solving and Ownership: A thoughtful, detail-oriented approach to troubleshooting, validating results, documenting decisions, and following work through delivery. · AI and Emerging Tools: Experience with Snowflake Cortex, AI agents, or generative AI solutions is preferred. Familiarity with Claude Code, GitHub Copilot, or other AI-assisted and agentic development tools is a plus, along with a willingness to learn and apply them responsibly. · Industry Background: Experience in insurance, financial services, or another regulated environment is preferred, but not required. You can be who you are We are committed to a culture of diversity and inclusion that embraces the authenticity of all employees, partners and communities. We support all employees to thrive and achieve their fullest potential. What’s life like at Pacific Life? Visit Instagram.com/lifeatpacificlife. #LI-KP1 Base Pay Range: The base pay range noted represents the company’s good faith minimum and maximum range for this role at the time of posting. The actual compensation offered to a candidate will be dependent upon several factors, including but not limited to experience, qualifications and geographic location. Also, most employees are eligible for additional incentive pay. $103,140.00 - $126,060.00 Your Benefits Start Day 1 Your wellbeing is important to Pacific Life, and we’re committed to providing you with flexible benefits that you can tailor to meet your needs. Whether you are focusing on your physical, financial, emotional, or social wellbeing, we’ve got you covered. Prioritization of your health and well-being including Medical, Dental, Vision, and Wellbeing Reimbursement Account that can be used on yourself or your eligible dependents Generous paid time off options including: Paid Time Off, Holiday Schedules, and Financial Planning Time Off Paid Parental Leave as well as an Adoption Assistance Program Competitive 401k savings plan with company match and an additional contribution regardless of participation You Can Be Who You Are We are committed to a culture of diversity and inclusion that embraces the authenticity of all employees, partners and communities. We support all employees to thrive and achieve their fullest potential. What’s life like at Pacific Life? Visit Instagram.com/lifeatpacificlife EEO Statement: Pacific Life Insurance Company is an Equal Opportunity /Affirmative Action Employer, M/F/D/V. If you are a qualified individual with a disability or a disabled veteran, you have the right to request an accommodation if you are unable or limited in your ability to use or access our career center as a result of your disability. To request an accommodation, contact a Human Resources Representative at Pacific Life Insurance Company.