Sr. Data Engineer

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Here you can join a team who is passionate about serving others, has a desire to do good, and shares a deep love of people. You can engage in meaningful work that impacts your community. You can challenge yourself and grow in your career. And, you can rest assured that your wellbeing and prosperity are our priority.

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Under the general supervision of the Data Analytics & Governance Manager/Team Leader, the Sr. Data Engineer plays a key role in supporting the enterprise data infrastructure and systems required for data storage, processing, and analysis. While the third-party vendor is responsible for designing the core data warehouse and managing data ingestion from major systems, the Sr. Data Engineer will assist the data warehouse vendor with the establishment of new data sources and provide support for any maintenance and troubleshooting required.

This includes focusing on integrating smaller or supplemental data sources into the Azure-based data warehouse and Databricks analytics platform, collaborating with internal teams to identify, model, and automate the ingestion of these data sources, and ensuring they meet organizational standards for data quality, governance, and security. Additionally, the Sr. Data Engineer partners closely with business leaders and executives to help define and advance the vision for managing data as a strategic business asset, aligning data management practices with organizational goals and driving value through effective data stewardship.

• Represent the Data Intelligence department in projects and committees as assigned
• Lead the design, development, and optimization of data pipelines for extracting, transforming, and loading data from diverse sources into the third-party data warehouse on Azure
• Collaborate with data analysts, BI analysts, data quality and data stewards, and IT professionals to develop and maintain scalable data models and analytical solutions
• Integrate data from databases, APIs, and external systems, ensuring consistency, integrity, and quality throughout the process
• Implement and monitor data governance frameworks, including data validation, cleansing, aggregation, and enrichment techniques
• Establish and enforce data quality checks, validations, and compliance with policies and procedures
• Optimize data processing workflows for performance, scalability, and efficiency; resolve bottlenecks and enhance query performance
• Design, develop, and maintain scalable data engineering solutions using Databricks, including Spark-based transformations, notebooks, and jobs
• Apply Databricks best practices for cluster configuration, job orchestration, performance tuning, and cost-aware design
• Implement medallion-style data architectures (Bronze, Silver, Gold) to support governed and analytics-ready datasets
• Enable and optimize data pipelines to support AI, machine learning, and advanced analytics use cases, fostering innovation across the organization
• Identify opportunities to leverage emerging technologies and innovative data engineering approaches for enhanced business insights and improved decision-making
• Support the ongoing strategic planning and monitoring process for data intelligence and data governance
• Educate and train stakeholders on data warehouse solutions, data governance, and best practices
• Maintain expert-level knowledge of core operating systems, data warehouse platforms, and data intelligence tools

• Advanced knowledge of Databricks for data engineering workloads, including Apache Spark, job orchestration and best practices such as layered data architectures, incremental processing, and optimization techniques
• Ability to comfortably utilize modern cloud-based data integration tools within Azure (e.g.,…