Data Product and Integration Analyst
About the role
The Data Product and Integration Analyst serves as a key connector between business stakeholders, analytics teams, data engineering, and technology partners to strengthen how enterprise data is defined, integrated, governed, and used. This role is responsible for helping create trusted, curated data assets that support customer segmentation, business reporting, analytics, and informed decision-making across critical policy, customer, and risk-related domains.
Responsibilities
- Data Integration & Management
- Design and maintain curated datasets that integrate data across multiple systems and domains supporting customer segmentation, and critical business reporting needs.
- Partner with data engineering teams to identify, source, and transform data from multiple systems into trusted enterprise data assets.
- Validate data mappings, lineage, and business rules to ensure accuracy, consistency, and traceability across data domains.
- Support the development and maintenance of data products that enable reporting, analytics, and informed business decision-making.
- Data Governance & Stewardship
- Apply enterprise data governance principles to strengthen data quality, integrity, consistency, and usability.
- Develop and maintain business metadata, data dictionaries, business glossaries, and lineage documentation.
- Define and monitor data quality controls, identify issues, and coordinate remediation activities with appropriate stakeholders.
- Partner with business and technology stakeholders to establish common definitions and governance standards across data domains.
- Business Translation & Requirements Management
- Act as a liaison between business stakeholders and technical teams, translating business needs into clear, actionable data requirements.
- Analyze business processes to understand how data is generated, consumed, and used across the organization.
- Facilitate discussions to align stakeholders on data definitions, requirements, priorities, and expected outcomes.
- Partner with reporting and analytics teams to ensure data solutions support business objectives and decision-making needs.
- Analytics & Continuous Improvement
- Identify opportunities to improve data accessibility, data quality, process efficiency, and governance practices.
- Perform exploratory analysis to validate business assumptions and support strategic initiatives.
- Recommend enhancements to data models, data flows, and governance processes.
- Serve as a subject matter resource for data assets within assigned business domains.
- Collaboration & Leadership
- Build strong relationships across business, analytics, data engineering, and technology teams.
- Provide guidance to team members and stakeholders on data governance standards and best practices.
- Lead small projects or workstreams involving data integration, governance, or process improvement.
Requirements
- 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 in a dynamic environment.
- Minimum of 5 years’ experience with SQL, including authoring highly complex queries to extract, transform, and analyze large data sets.
- Minimum of 3 years’ experience using Power BI, with 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, including familiarity with data warehouse, data lake, and modern data architecture concepts.
- Strong understanding of data governance, data quality, metadata management, and data lineage concepts, including familiarity with enterprise data catalog and governance platforms.
- Experience with Git-based source code management tools and practices.
- Advanced Microsoft Excel skills, including developing pivot tables, connecting to external data sources, and automating tasks with VBA.
- Experience with Agile delivery methodologies.
Qualifications
- Strong analytical and problem-solving skills, including the ability to apply quantitative and qualitative insights to support business strategy and effective execution.
- A strong sense of urgency and accountability, with a consistent focus on delivering high-quality work within deadlines.
- Ability to manage multiple and changing priorities independently while maintaining a drive for results in a fast-paced environment.
- Excellent communication skills, including the ability to deliver clear and effective verbal and written communications to both technical and non-technical audiences.
- Understanding, analyzing, and documenting complex business processes.
- Translate business requirements into practical technical data solutions.
- Teamwork & Collaboration: Build relationships and collaborate effectively with cross-functional teams, influencing outcomes and contributing as a strong team player.
- Excellent stakeholder management and cross-functional collaboration skills.
Skills
- Master’s degree in Data Analytics or a related discipline.
- Experience supporting customer segmentation or advanced analytics initiatives.
- Experience migrating legacy data systems to Azure or other cloud platforms.
- Experience leveraging big data technologies such as Azure Databricks to process large datasets, enable advanced analytics, and increase data throughput.
- Advanced Power BI experience designing and implementing interactive dashboards for executive leadership to enable real-time, data-driven decision-making.
- Python or R experience building predictive models to forecast customer or claims experience.
- Database and ETL experience developing and maintaining SQL Server databases and ETL pipelines that support seamless integration of diverse data sources.
- Experience using Alteryx to automate complex data preparation workflows, streamline ETL processes, and improve data accuracy for analytics and reporting.
- Familiarity with Apache Airflow for workflow orchestration and data pipeline management.
- Experience working with insurance, policy administration, risk management, or customer data domains.
- Long Term Care insurance product and claims process knowledge, including a strong understanding of LTC insurance products and claims workflows.
Benefits
Competitive Compensation & Total Rewards
Incentives
Comprehensive Healthcare Coverage
Multiple 401(k) Savings Plan Options
Auto Enrollment in Employer-Directed Retirement Account Feature (100% employer-funded!)
Generous Paid Time Off – Including 12 Paid Holidays, Volunteer Time Off and Paid Family Leave
Disability, Life, and Long Term Care Insurance
Tuition Reimbursement, Student Loan Repayment and Training & Certification Support
Wellness support including gym membership reimbursement and Employee Assistance Program resources (work/life support, financial & legal management)
Caregiver and Mental Health Support Services