Associate Information Data Architect (HYBRID)

Hanover Insurance Group•Howell, MI

5d•Hybrid

About The Position

The Associate Information Data Architect plays a key role in delivering trusted, high‑quality analytics, data products, and insights that support strategic and operational decision‑making across the organization. Working within a modern Azure-based data ecosystem (ADF, Synapse, ADLS, Azure SQL, Python), this role transforms complex data into curated datasets, automated reporting, and actionable intelligence for teams across a wide range of business domains. The Associate Information Data Architect collaborates with business stakeholders, architects, and engineering teams to translate requirements into scalable analytical solutions; design and govern KPI logic; validate data quality; and support both legacy (Informatica) and cloud native data platforms. Success in this role requires the ability to conceptualize solutions end-to-end, innovate within evolving cloud and data environments, drive results under tight timelines, build consensus across diverse stakeholders, and communicate complex concepts clearly to both technical and business audiences.

Requirements

Bachelor’s degree preferred.
Authorization to work in the United States without current or future sponsorship (U.S. citizen or lawful permanent resident).
2+ years of experience in a related field such as data engineering, ETL, data modeling, analysis, validation, reporting, or analytical solution delivery.
Strong proficiency with SQL for data analysis, data profiling and quality with large and complex datasets.
P&C insurance experience is strongly preferred, including understanding of operational and financial metrics.
Strong analytical and problem‑solving skills.
Advanced Excel, Power BI and other visualization tools; ability to translate data into meaningful insights.
Excellent written and verbal communication skills.
Strong time management, prioritization, and organizational skills.
Knowledge of technical mapping, including database schema, XML schema, and JSON schema.
Hands-on experience with Azure Data Factory, Synapse (SQL & Spark), ADLS, Azure SQL, and Azure DevOps (CI/CD).
Python experience for data wrangling, XML/JSON parsing, XPath, automation, and validation.
Experience creating semantic models and analytical datasets for BI platforms.
Understanding of KPI design, data governance, lineage, and business glossary concepts.
Ability to work across legacy (Informatica) and cloud platforms and validate logic during migrations.
Ability to plan for future capability needs and continuous improvements.

Nice To Haves

Data quality frameworks and automated testing with SQL/Python.
Synapse Spark / PySpark; Delta Lake and notebook development.
Experience with Microsoft Fabric (datasets, pipelines, governance).
Exposure to Microsoft Purview or similar metadata/lineage tools.
Experience with Parquet, partitioning, and performance optimization in lakehouse architectures.
Exposure to Azure DevOps CI/CD (YAML, Git branching).
Exposure to Event streaming (Event Hubs, Service Bus) and APIs/Web Services (REST/SOAP).

Responsibilities

Translate reporting and analytical requirements into analytical datasets, metric definitions, and reporting solutions.
Design and document source‑to‑target mappings, transformation logic, and data lineage for cross-system integrations.
Conduct deep‑dive data analysis to validate logic, resolve discrepancies, and support modernization or migration initiatives.
Respond to ad hoc and urgent requests by delivering accurate, timely information in a fast-paced environment.
Communicate complex data concepts clearly through written and verbal channels for both technical and business audiences.
Collaborate with product owners to define and document KPIs, metric logic, and shared business rules.
Create and maintain curated analytics datasets (SQL views, tables, semantic layers) for dashboards and self-service analytics.
Perform data profiling, quality checks, and reconciliation using SQL and Python to ensure accuracy and completeness.
Parse, transform, and validate XML/JSON using Python, XPath, and schema rules; ensure consistency across systems.
Maintain source‑to‑target mappings supporting Azure Data Factory, Synapse, and Informatica workflows.
Improve analytics performance through query optimization, semantic modeling, and scalable dataset design.
Support data governance through documentation, lineage tracking, and adherence to data management standards.
Collaborate with Data Engineering to translate requirements into cloud-based data pipelines (ADF, Synapse, Informatica).
Work with architecture and engineering teams to align datasets with enterprise data models and Azure standards.
Support Azure and Fabric monitoring (pipeline health, data freshness, validation checks) to ensure SLA adherence.
Validate and analyze data stored in ADLS containers, ensuring correct structure and schema.
Work with Delta Lake and Parquet files to perform integrity checks and ensure consistency across storage layers.
Conduct reconciliation and quality verification as data moves through cloud storage zones.
Contribute to tool enhancements, process improvements, and innovation initiatives.