Sr Data Management Analyst
Listed on 2026-06-28
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IT/Tech
Data Engineering, Data Analyst, Data Warehousing
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 Sr Data Management Analyst to join our team in Newport Beach, CA. The Sr Data Management Analyst role is a strong functional, engineering‑technical, and analytics‑focused role responsible for building and operationalizing scalable data quality and observability framework, data profiling tools and processes, data governance, and providing services and solutions aligned with Pacific Life’s PL Data Management strategy and Data Governance organization for Workforce Benefits (WBD).
This role combines data engineering, data analysis, and data quality management to ensure reliable, high‑quality, and trusted data across enterprise data platforms.
- Lead Data Quality and Governance for Workforce Benefits Division (WBD), manage asset certification program for data, data metrics, reports, and a multi‑faceted communication and engagement plan with the WBD data community.
- Partner with data architects, engineers, analysts, and business stakeholders to gather requirements and translate business needs into clear technical solutions.
- Lead requirements workshops, backlog refinement, and stakeholder discussions; document business, functional, and technical requirements.
- Implement data observability and data quality monitoring frameworks, including automated checks, anomaly detection, and alerting mechanisms across critical data pipelines.
- Perform deep data analysis using SQL and Python and profiling techniques to identify anomalies, data gaps, and inconsistencies across source‑to‑target systems.
- Develop and maintain data quality metrics, scorecards, and monitoring dashboards to track data reliability and pipeline health.
- Conduct root cause analysis and remediation of data issues, working across upstream and downstream systems.
- Design and develop scalable data solutions, including data models, source‑to‑target mappings, ETL/ELT.
- Collaborate with engineering teams on code reviews, testing, CI/CD processes, and deployment best practices.
- Support data governance initiatives, including metadata management, data lineage, data certification, and business glossary maintenance.
- Ensure compliance with data standards, controls, and regulatory requirements for sensitive data (PII/PHI).
- Work within Agile delivery teams to prioritize, manage, and execute work effectively.
- BS in Computer Science, Mathematics, Finance, or related field. Master’s degree preferred.
- Minimum of 6+ years’ of professional experience in Data analysis, Data Quality, Engineering, or related roles.
- Expert level SQL and strong Python programming skills; hands‑on experience with SQL for data analysis, validation, and troubleshooting data issues.
- Experience building or supporting data pipelines, ETL processes, or data workflows.
- Experience implementing data quality monitoring, observability frameworks, or automated controls.
- Experience working with cloud‑based data platforms (AWS, Azure, Snowflake, etc.).
- Strong experience with data profiling, anomaly detection, and root cause analysis.
- Experience working in Workforce Benefits (WBD), Insurance, or Healthcare data domains.
- Experience working on complex business/technology initiatives within and across multiple verticals/domains.
- Ability to analyze complex data issues and determine appropriate policies, standards, and solutions to enhance the experience for data users.
- Experience with regulated data environments (PII/PHI).
- Experience in Workforce benefits domain.
- Data Management Professional (CDMP), AWS…
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