Data Engineer with Databricks 100% Remote No Sponsorship candidates Long Term contract that will likely convert to an FTE Job Summary: We are seeking a skilled and motivated Data Engineer with hands-on experience in Databricks and foundational knowledge of .NET development. The ideal candidate will play a key role in building and optimizing data pipelines, designing scalable ETL/ELT workflows, and supporting our analytics infrastructure. This role bridges modern data engineering tools with application development, making it ideal for candidates with hybrid skill sets. Key Responsibilities: • Design, build, and maintain robust data pipelines using Databricks, Apache Spark, and Delta Lake. • Work closely with data scientists, analysts, and business stakeholders to understand data needs and deliver efficient solutions. • Optimize and monitor data workflows for performance, scalability, and reliability. • Integrate structured and unstructured data sources into our data lake and warehouse environments. • Develop custom components and services using .NET (C#) for data ingestion, APIs, or automation tasks as needed. • Ensure data security, compliance, and governance standards are met. • Participate in code reviews, testing, and documentation of engineering solutions. • Collaborate in agile ceremonies and contribute to sprint planning and estimation. Required Qualifications: • Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field. • 10+ years of experience as a Data Engineer or in a similar role. • Proficiency in Databricks, Apache Spark, and Delta Lake. • Strong SQL skills and familiarity with query optimization techniques. • Experience with cloud platforms such as Azure, AWS, or GCP (preferably Azure Databricks). • Working knowledge of .NET / C# for service development or integration tasks. • Familiarity with version control systems (e.g., Git), CI/CD pipelines, and Agile methodologies Preferred Qualifications: • Experience with Azure Data Factory, Synapse, or other ETL tools. • Exposure to REST APIs, Microservices, or data-driven application architecture. • Knowledge of data warehousing, data modeling, and data governance principles. Comfortable with scripting languages (e.g., Python, PowerShell) for automation.