Data Engineer

Job Summary We are seeking a Data Engineer to support a data modernization initiative focused on improving enterprise data accessibility, accelerating analytics delivery, and enabling future AI capabilities. This role is responsible for designing and developing scalable data pipelines, building modern cloud-based data solutions, and supporting enterprise analytics initiatives using Databricks and Microsoft Azure. The ideal candidate will have strong expertise in Databricks, Azure Data Factory, Python, SQL, and ETL/ELT development within modern cloud data platforms. Key Responsibilities Design, develop, and maintain scalable data pipelines using Databricks, Azure Data Factory (ADF), Python, and SQL. Build, optimize, and maintain ETL/ELT processes to ingest, transform, and aggregate data from multiple enterprise and external data sources. Develop robust data consumption layers to improve data accessibility for business intelligence, analytics, and AI initiatives. Collaborate with architects, data engineers, and business stakeholders to deliver scalable data products and accelerate analytics initiatives. Design and optimize datasets that support Power BI reporting and enterprise analytics solutions. Support enterprise-wide analytics initiatives by integrating, cleansing, and standardizing data across multiple systems. Contribute to data architecture decisions and establish engineering best practices within Azure and Databricks environments. Enhance data usability, self-service analytics capabilities, and overall user experience across the enterprise. Participate in code reviews, testing, deployment, and continuous platform optimization activities. Monitor, troubleshoot, and optimize data pipelines to ensure performance, reliability, and scalability. Develop and maintain technical documentation throughout the data engineering lifecycle. Required Qualifications Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent professional experience. Minimum of 3 years of experience in Data Engineering, ETL development, or data platform engineering. Strong hands-on experience with Databricks. Proficiency in Python and SQL. Experience designing, developing, and maintaining ETL/ELT pipelines. Hands-on experience with Azure Data Factory (ADF). Experience working with Azure or other cloud-based data platforms and modern data architectures. Experience with data ingestion, transformation, data modeling, and data integration processes. Experience supporting analytics and reporting teams through curated datasets and optimized data models. Strong understanding of cloud-based data engineering best practices. Strong analytical, problem-solving, and communication skills. Ability to collaborate effectively with technical teams and business stakeholders. Preferred Qualifications Experience supporting workers' compensation, insurance, healthcare, financial services, or other highly regulated industries. Experience with Azure Data Lake or other cloud-based data lake environments. Experience supporting Power BI reporting and analytics solutions. Familiarity with GitHub, CI/CD pipelines, and DevOps practices. Experience with containerization technologies and Kubernetes. Experience supporting data science, machine learning, or AI initiatives through scalable data engineering solutions. Education: Bachelors Degree