SENIOR DATA ENGINEER

General Description:

The Senior Data Engineer plays a critical leadership role within the Information Technology organization, partnering closely with data and analytics leadership to design, build, and evolve scalable, reliable, and secure data platforms that support enterprise analytics, reporting, and advanced data initiatives. This role is responsible for driving technical standards, architectural decisions, and best practices across data engineering efforts, while ensuring high levels of data availability, quality, and accessibility across business domains.

The Senior Data Engineer works independently on complex initiatives, translates business and analytical requirements into robust technical solutions, and serves as a technical mentor to other data engineers and analysts. This position contributes significantly to data platform modernization, data product development, and the enablement of self-service analytics, AI/ML, and future-state data capabilities.

Essential Duties and Responsibilities:

Data Platform Management

Provide senior-level support and ongoing optimization of the Enterprise Data Mesh, ensuring accuracy, performance, scalability, and reliability of data pipelines processes and downstream data consumption.

Data Platform Architecture

Lead the architecture, design, and implementation of scalable on-premises and/or cloud-based enterprise data platforms, integrating Guidewire and non-Guidewire data sources to support enterprise analytics and data products.

Advanced Data Integration & Engineering

Design, develop, and oversee robust ETL/ELT pipelines using modern tools and frameworks, such as Microsoft Fabric, TimeXtender, or Databricks. Establish patterns for ingestion, transformation, orchestration, and monitoring of complex data workflows.

Data Modeling & Technical Architecture

Design and govern optimized data models for structured and semi-structured data, supporting reporting, analytics, operational use cases, and AI/ML initiatives. Influence architectural standards and long-term data strategy.

Data Governance, Quality & Security

Champion best practices for data governance, metadata management, data quality, lineage, and security. Ensure compliance with regulatory and internal standards across all enterprise data assets.

Advanced Analytics Enablement

Enable self-service analytics, near-real-time data processing, and AI/ML-driven use cases by integrating data lakes, lakehouse architectures, streaming technologies, and modern data storage paradigms.

Collaboration, Mentorship & Leadership

Act as a trusted technical partner to IT, analytics teams, and business stakeholders. Mentor junior data engineers and analysts, review designs and code, and promote a culture of engineering excellence and data-driven decision-making.


Operational Excellence

• Monitor the task queue, take, and update tickets as directed by your supervisor.
• Successfully engage in multiple initiatives simultaneously.
• Contributes to the development of project plans and may assign and monitor tasks.
• Assist in the development and generation of new reports to be provided to senior management across functional departments.
• Performs other duties as required.

Supplemental Information:

This job description has been prepared to indicate the general nature and level of the work that the employees perform within their classification. This description is not and cannot be interpreted as an inventory of all the duties, tasks, responsibilities, and qualifications required for the employees assigned to this job.

Education and / or Experience:

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or a related field
• 8+ years of progressive experience in data engineering, data architecture, or related roles, preferably within the insurance industry
• Strong expertise in Guidewire InsuranceSuite database schemas (PolicyCenter, BillingCenter, ClaimCenter) is a plus
• Proven ability to analyze, learn, and integrate complex data source models into enterprise data platforms
• Hands-on experience implementing cloud-based data platforms in Azure, including data lakehouse architectures
• Advanced proficiency with modern ETL/ELT tools (e.g., SSIS, Azure Data Factory) and database technologies (SQL Server, Databricks, etc.)
• Experience with big data processing, streaming technologies (Kafka, Spark, Flink), and API-driven integrations
• Strong understanding of data security, compliance, and governance best practices (GDPR, CCPA, SOC 2, etc.)
• Familiarity with BI and analytics tools such as Power BI, Tableau, or Looker
• Experience with Data Mesh architecture is a plus
• Knowledge of machine learning concepts, data pipelines for ML, and MLOps is a plus
• Familiarity with ticketing systems such as Atlassian Jira
• Demonstrated ability to work independently, prioritize effectively, and deliver high-quality solutions under tight deadlines
• Strong organizational skills, attention to detail, and adaptability in a changing environment
• Excellent verbal and written communication skills, with the ability to interact professionally with executives, managers, and technical stakeholders
• Proficiency in Microsoft Office (Excel, Word, PowerPoint)

Licenses and / or Certifications:

Azure Data Engineer Associate or higher preferred.