PL Ops - Data Engineer

Join a remote Data Engineer II role with The Hanover Insurance Group and contribute to Personal Lines Operations by building and maintaining Azure Data Factory pipelines and an on-prem SQL Server data environment. You will balance production support with new development while advancing data quality, monitoring, and release practices. The position offers a salary range of USD 75,000 to 100,000 per year and requires a Bachelor’s degree with at least six years of experience.

Benefits

• Medical, dental, vision, life, and disability insurance
• 401K with company match
• Tuition reimbursement
• PTO
• Company paid holidays
• Flexible work arrangements
• Cultural Awareness Day in support of IDE
• On-site medical/wellness center (Worcester only)

Career development

This is a true career opportunity with growth support through on-the-job experiences, personalized coaching, and a robust learning and development program. Professionals at every level are encouraged to grow and advance.

Responsibilities

• Provide production support and daily health checks for scheduled ADF pipelines
• Design new pipelines and enhance existing ones to improve resiliency, maintainability, and scalability
• Implement data validation controls, enhance monitoring and alerts, and help define SLAs for data freshness and availability
• Establish foundational data engineering SDLC practices, including Git usage, Dev to Prod promotion, and a formal release process
• Coordinate cross-team dependencies and design dependency-aware orchestration and readiness checks
• Contribute to future-state Azure data strategy recommendations (e.g., Data Lake/Blob Storage, notebooks) and support migration planning from on-prem SQL Server to cloud databases
• Azure/Fabric Data Factory engineering
• Design and maintain curated SQL tables and views for analytics and reporting; optimize refresh performance and downstream usability
• Develop and maintain ADF pipelines (Copy activities and Data Flows) with consistent logging, error handling, retries, and notifications
• Implement parameterization and reusable components to reduce duplication and accelerate enhancements
• Implement incremental load and backfill strategies suited to data volume
• Production support and reliability: monitor daily pipeline execution and triage incidents to restore processing
• Perform root-cause analysis for failures and recurring issues; implement preventative controls and standardized patterns
• Create and maintain operational runbooks for critical pipelines and common support scenarios
• Data quality, validation, and trust: build automated validation routines and reconciliation checks; collaborate with analysts to define business rules and quality thresholds
• Document data definitions, transformations, and lineage to improve transparency
• Stakeholder collaboration and dependency management: work with Operations Data Analysts, business stakeholders, and partner analysts to deliver datasets for Power BI models and other analytics; align dependency readiness signals and timelines; provide technical coaching and mentoring

Key measures of success

• Pipelines meet SLAs and deliver on time
• Pipeline success rate with reduced manual intervention
• Time to detect and resolve ETL failures (MTTD/MTTR)
• Improvements in query performance, runtime, and cost efficiency
• Reduction in recurring data quality defects; data completeness and accuracy
• Documentation coverage, including runbooks and data dictionary completeness

Requirements

• Bachelor’s Degree preferred in a related field
• 6+ years of experience in data engineering, ETL/ELT, or related roles
• Hands-on experience building and supporting production pipelines in Azure Data Factory
• Strong SQL/T-SQL skills and experience with SQL Server environments supporting analytics and reporting
• Advanced data modeling capabilities
• Experience integrating data from multiple sources including databases, flat files/SFTP, and APIs/vendor feeds
• Familiarity with Azure data platform components (Data Lake/Blob Storage, notebooks) and/or cloud migration planning
• Strong troubleshooting, root-cause analysis, and operational ownership mindset
• Ability to work directly with stakeholders to gather requirements and translate them into technical solutions
• Excellent communication and documentation skills for presenting findings and translating data into understandable documents

Technologies

• Azure Data Factory
• SQL Server
• T-SQL
• Data Lake/Blob Storage
• Notebooks
• Power BI
• Git
• CI/CD
• Python
• PowerShell
• SFTP