Data Product & Integration Analyst

Requirements Must have:

• – Bachelors degree in Information Systems, Data Analytics, Computer Science, Business, Statistics, or a related discipline, or equivalent professional experience.
• – At least 5 years of experience in data analysis, business analysis, data governance, data stewardship, data modeling, or data engineering in a fast-moving environment.
• – At least 5 years of hands-on SQL experience, including writing highly complex queries to extract, transform, and analyze large datasets.
• – At least 3 years of Power BI experience, with strong knowledge of semantic models, dataflows, gateways, and publishing to Power BI Server.
• – At least 3 years of scripting experience with languages such as Python or R.
• – At least 3 years supporting data governance, metadata management, or data quality initiatives.
• – At least 3 years working in Azure or another cloud environment with related data services, including familiarity with data warehouses, data lakes, and modern data architecture concepts.
• – Strong understanding of data governance, data quality, metadata management, and data lineage, including familiarity with enterprise data catalog and governance platforms.
• – Experience using Git-based source code management tools and practices.
• – Advanced Microsoft Excel skills, including pivot tables, external data connections, and VBA automation.
• – Experience working with Agile delivery methodologies.
• – Strong critical thinking and problem-solving skills, with the ability to combine quantitative and qualitative insights to support business strategy and execution.
• – Strong results orientation, accountability, and urgency, with a consistent focus on delivering high-quality work on time.
• – Ability to self-manage multiple changing priorities in a fast-paced environment while staying focused on outcomes.
• – Excellent verbal and written communication skills for both technical and non-technical audiences.
• – Ability to understand, analyze, and document complex business processes.
• – Ability to translate business requirements into practical technical data solutions.
• – Strong teamwork, relationship‑building, stakeholder management, and cross‑functional collaboration skills.

• – Nice to have:
  Masters degree in Data Analytics or a related field.
• – Nice to have:
  Experience supporting customer segmentation or advanced analytics initiatives.
• – Nice to have:
  Experience migrating legacy data systems to Azure or other cloud platforms.
• – Nice to have:
  Experience with big data technologies such as Azure Databricks.
• – Nice to have:
  Advanced Power BI experience building interactive executive dashboards.
• – Nice to have:
  Python or R experience developing predictive models for customer or claims outcomes.
• – Nice to have:
  Experience building and maintaining SQL Server databases and ETL pipelines.
• – Nice to have:
  Experience using Alteryx to automate data preparation and improve analytics workflows.
• – Nice to have:
  Familiarity with Apache Airflow for workflow orchestration and pipeline management.
• – Nice to have:
  Experience in insurance, policy administration, risk management, or customer data domains.
• – Nice to have:
  Knowledge of Long Term Care insurance products and claims processes.

• – Design and maintain curated datasets that combine data from multiple systems and domains to support customer segmentation and business reporting.
• – Partner with data engineering teams to source, transform, and consolidate data into trusted enterprise assets.
• – Validate data mappings, lineage, and business rules to ensure accuracy, consistency, and traceability.
• – Help develop and sustain data products that support reporting, analytics, and business decision‑making.
• – Apply enterprise data governance principles to improve data quality, integrity, consistency, and usability.
• – Create and maintain business metadata, data dictionaries, business glossaries, and lineage documentation.
• – Define and monitor data quality controls, identify issues, and coordinate remediation with stakeholders.
• – Work with business and technology partners to establish shared definitions and governance standards.
• – Serve as a bridge between business stakeholders and technical teams by…