Data Engineer

Role focus: Hands-on Databricks, Python, SQL, data pipelines, applications, automation, analytics, and Power BI. These are not primarily reporting or dashboard-development roles. Position Overview We are seeking two experienced Senior Data & Analytics Engineers to develop, integrate, and maintain enterprise data and analytics solutions. The selected professionals will work broadly across the data environment, including data engineering, Databricks applications, data warehousing, automation, analytics, and reporting. There can be some variation between the two hires. One resource may lean more heavily toward hands-on Databricks, application development, and engineering, while the other may bring additional strength in analytics solution development, data warehousing, ETL/ELT, Power BI, and stakeholder engagement. Key Responsibilities Design, develop, and maintain scalable data solutions using Databricks. Build and support ETL/ELT jobs, data pipelines, and data-integration workflows. Develop applications, utilities, and automated processes using Python and SQL. Maintain and enhance existing applications and production data solutions. Design and support data warehouses, data models, and integrated data structures. Develop Power BI dashboards, reports, semantic models, and analytics solutions. Work effectively with large, complex datasets from multiple systems and sources. Monitor solutions for performance, reliability, accuracy, and data quality. Troubleshoot and resolve pipeline, application, integration, and reporting issues. Gather requirements and translate business needs into scalable technical solutions. Create and maintain technical documentation for applications, pipelines, models, and processes. Collaborate directly with business users, clients, analysts, developers, and technical teams. Required Qualifications Strong hands-on Databricks experience. Advanced proficiency with Python and SQL. Experience building and maintaining production ETL/ELT jobs and data pipelines. Experience with application development, maintenance, and production support. Strong understanding of data warehousing, data integration, and data modeling. Experience developing dashboards and reporting solutions with Power BI. Experience automating processes and improving business or technical workflows. Strong troubleshooting, root-cause analysis, and data-quality skills. Ability to gather requirements and work directly with business or client stakeholders. Ability to work independently and communicate effectively across technical and business teams. Preferred Qualifications Experience supporting utility, energy, infrastructure, or another asset-intensive industry. Experience with cloud-based data platforms and enterprise data environments. Familiarity with APIs, application integrations, and structured and unstructured data sources. Experience optimizing Databricks workloads, SQL queries, and data pipelines. Understanding of data governance, security, quality, and documentation practices. Complementary Candidate Profiles Python-based application and automation development Application maintenance and production support Data integration and performance optimization Analytics Solutions & Data Warehousing Focus Data warehousing and dimensional data modeling ETL/ELT and data-integration development Requirements gathering and stakeholder engagement Ideal Candidate The ideal candidate is a broad, hands-on data professional who can contribute across the full solution lifecycle—from raw data ingestion and pipeline development through applications, automation, analytics, reporting, maintenance, and client support. Both hires should have a strong foundation in Databricks, Python, SQL, data pipelines, and Power BI. #J-18808-Ljbffr