Senior Data Engineer
Location: Dallas, TX

Position Summary

We’re looking for an experienced Senior Data Engineer to join our growing Data Insights & Analytics team. You’ll play a critical role in designing, building, and scaling the data infrastructure that powers our core products and client-facing insights.

In this role, you’ll architect data solutions using modern Azure technologies, including Microsoft Fabric, Synapse, Azure SQL, and Data Factory. You'll develop robust pipelines to process, transform, and model complex insurance data into structured, reliable datasets that fuel analytics, dashboards, and data science products.

In addition to your technical responsibilities, your daily routine will include participating in standup meetings, managing work items based on your capacity, collaborating with the team’s growing technology team to define new projects or initiatives, and engage in development activities. In addition to traditional data engineering tasks, you will directly interact with the teams developing the tools we utilize, enabling you to provide direct product feedback and witness your input driving changes in the products over time.

Key Responsibilities

Design and build robust, scalable ETL/ELT pipelines using Azure Data Factory, Synapse, and Microsoft Fabric
Model and transform raw insurance data into structured datasets for reporting and analytics use cases
Collaborate with analysts, engineers, and business stakeholders to align data solutions with company goals
Implement orchestration logic, metadata-driven processing, and Spark-based transformations (PySpark, Spark SQL)
Optimize performance of data workflows and pipelines to support real-time and batch processing scenarios
Drive best practices in data governance, documentation, code quality, and DevOps automation
Monitor production workloads, troubleshoot pipeline failures, and support live environments
Evaluate new Azure data services and tools for potential adoption

Key Skills & Expertise

Data Engineering: Advanced ETL/ELT experience with large, complex data sets
Azure Stack: Strong knowledge of Azure Data Factory, Synapse Analytics, Azure SQL, and Microsoft Fabric
Spark Ecosystem: Experience with Spark development using PySpark and Spark SQL (especially in Fabric notebooks)
Data Modeling: Expertise in dimensional modeling, normalization, and schema design
Coding Proficiency: Fluent in Python, SQL, Spark SQL, and scripting for orchestration and automation
Performance Tuning: Familiarity with optimizing query performance, parallel processing, and cloud-based workloads

Qualifications

Bachelor’s degree in Computer Science, Data Engineering, or related field (Master’s a plus)
5+ years of experience in data engineering or analytics engineering roles
3+ years working with Azure data services and cloud-native platforms
Experience with Microsoft Fabric is highly desirable
Proven ability to transform business requirements into scalable, maintainable data workflows
Experience working with Lloyd’s of London bordereaux data is a strong plus, particularly in contexts involving ingestion, validation, and transformation of complex insurance data sets.