The Hanover Insurance Group has been dedicated to delivering on promises for over 170 years, and they are currently seeking a Data Engineer II to join their Claims Analytics team. This role focuses on developing scalable data models and ETL pipelines while ensuring data quality and collaborating with cross-functional teams.
Responsibilities:
- Develop scalable and efficient data models, data structures, and ETL pipelines that support analytics, reporting, and downstream consumption
- Consistently prioritize data quality by implementing validation checks, monitoring accuracy and completeness, and clearly documenting data pipelines and processes
- Work with no or minimum supervision on assigned projects and effectively manage multiple tasks or projects simultaneously
- Collaborate with business partners and cross-functional teams on data/reporting requests
- Be accountable for successful outcomes related to designing, developing, implementing, optimizing, and maintaining data pipelines and solutions
- Work with an ownership mindset to design, implement, and continuously improve data governance, controls, and standards, ensuring the platform is secure, compliant, and scalable
- Prioritize work effectively by balancing business impact, technical risk, and domain knowledge to deliver the highest‑value outcomes
Requirements:
- Bachelor's degree or higher in Data Science, Mathematics, Statistics, Computer Science, Information Systems, Business Information Technology, or equivalent
- 5+ years professional experience in data engineering, data architecture, or data analytics
- Proficiency in the following languages: Advanced SQL, Python, Java, Scala (nice to have)
- Proficient in building SQL stored procedures, ETL pipelines using Azure Synapse (Synapse Pipelines / Data Factory)
- Holds active Azure DP-203 (Microsoft Certified: Azure Data Engineer Associate) or equivalent. Other Azure DP certifications or equivalents are also applicable
- Familiarity in insurance data (Claims data is highly preferred)
- Data Modeling: Creation of conceptual, logical, and physical data models for data objects, object attributes, and their relationships
- Analytical Skills: Data Engineers work with large amounts of data that will include facts, figures, and number crunching. You will need to profile the data and analyze it to find conclusions
- Communication Skills: Data engineers are often called to present their findings or translate the data into an understandable document. You will need to write and speak clearly, easily communicating complex ideas
- Critical Thinking: Data engineers must look at the numbers, trends, and data and come to new conclusions based on the findings
- Attention to Detail: Data is precise. Data engineers must make sure they are vigilant in their analysis to come to correct conclusions
- Math Skills: Data engineers need advanced math skills to estimate numerical data. Insurance experience required as well as insurance products
- Debugging Skills: Data engineers need the ability to analyze issues with components in our data solutions and come up with remediation plans
- Proven experience in data engineering, implementation of best practices for data storage, access, integration, transformation, etc., within Azure
- Proven experience using Databricks and delta live tables in a data engineering context
- Experience in optimizing data pipelines to account for scale, performance, reliability, and cost efficiency
- Demonstrated proficiency in relational, NoSQL, hierarchical, and entity relationship data modeling
- Experience in creating easy to consume documentation of data processes and solutions to aid in knowledge transfer and continuity
- Experienced in agile development methodologies, developing high quality code, and DevOps best practices
- Must be eligible to work in the United States without requiring sponsorship now or in the future (ie. lawful permanent residence or US citizen)