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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
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:
Licenses and / or Certifications:
Azure Data Engineer Associate or higher preferred.