Data Product and Integration Analyst

Genworth Financial

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Richmond, VA
Salary
$84,400–$127,000 / yr
Employment
Full-time
Posted
64 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $164k
This role $106k
$70k most similar roles pay here $216k

This role pays less than 92% of similar roles. Most pay $126,250–$201,600 — the shaded band above. At the midpoint, this role pays about $106k versus about $164k for comparable roles.

Based on 240 similar postings.

Employer

About Genworth Financial

Genworth Financial is a financial services company focused on mortgage insurance, long-term care insurance, and life insurance and annuity products to help people protect their financial well-being. Industry: Insurance & Financial Services

Genworth Financial currently has 24 open roles on FindRole.

Listed pay typically runs $120,900–$187,000 across 24 roles with salary data.

Most-posted roles

View all roles at Genworth Financial

At a glance

TL;DR · Data Product and Integration Analyst

The Data Product and Integration Analyst serves as a vital link between business stakeholders, analytics teams, data engineering, and technology partners to strengthen enterprise data governance and integration. This role focuses on creating trusted, curated data assets to support customer segmentation, risk-related domains, and strategic reporting. You will translate complex business needs into actionable requirements, validate data mappings, manage metadata, and oversee data quality controls. The ideal candidate possesses a background in information systems or data analytics and demonstrates proficiency in SQL for complex querying, Power BI for semantic modeling, and scripting languages like Python or R. Experience with Azure cloud environments, Git-based source code management, and advanced Excel is required. This role solves critical problems regarding data consistency and accessibility within the policy and risk management domains to enable informed decision-making across the organization.

What you'll do

  • Design and maintain curated datasets that integrate data across multiple systems for customer segmentation and reporting.
  • Partner with engineering teams to source and transform raw data into trusted enterprise assets.
  • Validate data mappings, lineage, and business rules to ensure accuracy and consistency across domains.
  • Develop and maintain metadata, data dictionaries, and business glossaries to support governance.
  • Translate complex business needs into actionable technical requirements for data engineering and technology teams.
  • Define and monitor data quality controls while coordinating remediation activities with stakeholders.
  • Identify opportunities to improve data accessibility, process efficiency, and overall governance practices.
  • Serve as a subject matter expert on data assets and provide guidance on best practices to team members.

What we're looking for

  • Bachelor's degree in Information Systems, Data Analytics, Computer Science, Business, Statistics, or a related field, or equivalent work experience.
  • Minimum of 5 years’ experience in data analysis, business analysis, data governance, data stewardship, data modeling, or data engineering.
  • Minimum of 5 years’ experience with SQL, including authoring complex queries to extract, transform, and analyze large datasets.
  • Minimum of 3 years’ experience using Power BI, including proficiency in semantic models, dataflows, gateways, and publishing to Power BI Server.
  • Minimum of 3 years’ experience with scripting languages such as Python or R.
  • Minimum of 3 years’ experience supporting data governance, metadata management, or data quality initiatives.
  • Minimum of 3 years’ experience working within Azure or other cloud environments and related data services.
  • Advanced Microsoft Excel skills including pivot tables, external data connections, and VBA automation.
  • Experience with Git-based source code management tools and Agile delivery methodologies.
  • Master's degree in Data Analytics or a related discipline (preferred).
  • Experience supporting customer segmentation, advanced analytics, or migrating legacy systems to cloud platforms (preferred).
  • Experience with big data technologies like Azure Databricks, Alteryx, or Apache Airflow (preferred).
  • Knowledge of insurance products, risk management, or long-term care claims processes (preferred).

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