Pacific Life Insurance
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 a Principal Analytics Engineer, you’ll play a crucial role in bridging the gap between data analysis and engineering. Your focus will be on creating robust data models, designing efficient pipelines, and enabling end-users to extract meaningful insights from complex datasets. If you’re passionate about data-driven decision-making and enjoy combining technical expertise with business acumen, this role might be a perfect fit for you.
How you’ll help move us forward: Thought Leadership: Stay engaged with cross industry data and analytics engineering thought leadership, synthesize key concepts, and drive practical adoption within the department. Upskilling and Collaboration: Act as a mentor to other engineers, promoting a culture of continuous learning and improvement. Lead workshops and training sessions on dbt, Snowflake, and other data engineering best practices. Foster a collaborative environment where knowledge sharing is encouraged. Documentation and Communication: Maintain clear and comprehensive documentation for data models, pipelines, and feature engineering processes. Communicate results, insights, and findings to stakeholders, including technical and non-technical audiences. Collaborate with cross-functional teams to align analytics efforts with business goals. Data Modeling: Design and develop modular data models using dbt Cloud that accurately represent business entities, relationships, and hierarchies. Optimize data structures for efficient querying and reporting. Collaborate with data scientists and analysts to understand their requirements and translate them into actionable data models. Data Pipeline Development: Build and maintain data pipelines to transform and process raw data from various sources (databases, APIs, logs, etc.). Ensure data quality, consistency, and reliability throughout the pipeline. Implement ELT processes using dbt and Snowflake to prepare data for analysis. Performance Optimization: Optimize data processing performance, considering factors like scalability, latency, and resource utilization. Monitor and troubleshoot data pipelines to ensure smooth operation. Identify bottlenecks and propose improvements. The experience you bring: Bachelor’s degree in Computer Science, Data Science, or related fields. 10+ years of experience as an Analytics Engineer, Data Engineer, or Data Scientist in a company with large, complex data sources. Expertise in SQL, dbt, Python, and other programming languages for data manipulation. Experience with data modeling, ETL/ELT processes, and database design. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Experience providing technical leadership and mentoring other engineers for best practices on analytics engineering. Expertise with AWS platform, services, and tools. Expertise in Snowflake. Experience with unstructured and streaming data. Familiarity with agile practices and tools (e.g., dbt, ADO). What makes you stand out: Experience in other database and data warehouse systems like Redshift, Athena, BigQuery, Oracle, MySQL, SQL Server, and Postgres a plus. Expertise building in dbt Cloud, Snowflake, and AWS. Expertise in mutual fund, annuity, or life insurance data. Demonstrated mentorship and collaboration skills. Capable of working across multiple initiatives at once. Confident interacting with various levels of business users. Data, Analytics, and other related certifications from Snowflake, AWS, or other vendors. You can be who you are.
People come first here. We’re committed to a diverse, equitable and inclusive workforce. Learn more about how we create a welcoming work environment through Diversity, Equity, and Inclusion at www.pacificlife.com. What’s life like at Pacific Life? Visit Instagram.com/lifeatpacificlife.
Benefits start Day 1.
Your wellbeing is important. We’re committed to providing 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 a 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. 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. $159,660.00 - $195,140.00
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We’re actively seeking a talented Analytics Engineer to join our Analytics Engineering team. As a Principal Analytics Engineer, you’ll play a crucial role in bridging the gap between data analysis and engineering. Your focus will be on creating robust data models, designing efficient pipelines, and enabling end-users to extract meaningful insights from complex datasets. If you’re passionate about data-driven decision-making and enjoy combining technical expertise with business acumen, this role might be a perfect fit for you.
How you’ll help move us forward: Thought Leadership: Stay engaged with cross industry data and analytics engineering thought leadership, synthesize key concepts, and drive practical adoption within the department. Upskilling and Collaboration: Act as a mentor to other engineers, promoting a culture of continuous learning and improvement. Lead workshops and training sessions on dbt, Snowflake, and other data engineering best practices. Foster a collaborative environment where knowledge sharing is encouraged. Documentation and Communication: Maintain clear and comprehensive documentation for data models, pipelines, and feature engineering processes. Communicate results, insights, and findings to stakeholders, including technical and non-technical audiences. Collaborate with cross-functional teams to align analytics efforts with business goals. Data Modeling: Design and develop modular data models using dbt Cloud that accurately represent business entities, relationships, and hierarchies. Optimize data structures for efficient querying and reporting. Collaborate with data scientists and analysts to understand their requirements and translate them into actionable data models. Data Pipeline Development: Build and maintain data pipelines to transform and process raw data from various sources (databases, APIs, logs, etc.). Ensure data quality, consistency, and reliability throughout the pipeline. Implement ELT processes using dbt and Snowflake to prepare data for analysis. Performance Optimization: Optimize data processing performance, considering factors like scalability, latency, and resource utilization. Monitor and troubleshoot data pipelines to ensure smooth operation. Identify bottlenecks and propose improvements. The experience you bring: Bachelor’s degree in Computer Science, Data Science, or related fields. 10+ years of experience as an Analytics Engineer, Data Engineer, or Data Scientist in a company with large, complex data sources. Expertise in SQL, dbt, Python, and other programming languages for data manipulation. Experience with data modeling, ETL/ELT processes, and database design. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Experience providing technical leadership and mentoring other engineers for best practices on analytics engineering. Expertise with AWS platform, services, and tools. Expertise in Snowflake. Experience with unstructured and streaming data. Familiarity with agile practices and tools (e.g., dbt, ADO). What makes you stand out: Experience in other database and data warehouse systems like Redshift, Athena, BigQuery, Oracle, MySQL, SQL Server, and Postgres a plus. Expertise building in dbt Cloud, Snowflake, and AWS. Expertise in mutual fund, annuity, or life insurance data. Demonstrated mentorship and collaboration skills. Capable of working across multiple initiatives at once. Confident interacting with various levels of business users. Data, Analytics, and other related certifications from Snowflake, AWS, or other vendors. You can be who you are.
People come first here. We’re committed to a diverse, equitable and inclusive workforce. Learn more about how we create a welcoming work environment through Diversity, Equity, and Inclusion at www.pacificlife.com. What’s life like at Pacific Life? Visit Instagram.com/lifeatpacificlife.
Benefits start Day 1.
Your wellbeing is important. We’re committed to providing 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 a 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. 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. $159,660.00 - $195,140.00
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