Databricks Engineer

This is a long-term contract (approximately 12 months) and is hybrid to Adelphi, MD. A background check will be required. The ideal candidate is a detail-oriented, analytical problem solver who enjoys tackling complex data challenges. They communicate clearly and collaborate effectively with cross-functional teams to deliver meaningful, data-driven solutions. They are adaptable, service-oriented, and curious, with a passion for modern data technologies and continuous improvement. Highly organized and proactive, they manage multiple priorities while maintaining a strong focus on quality, scalability, and innovation. Key Responsibilities • Implement and optimize data models within Databricks to support efficient querying, analytics, and reporting. • Design, develop, and maintain scalable ETL/ELT pipelines, with a strong emphasis on dimensional modeling and data quality. • Partner with engineering teams and business stakeholders to gather requirements and deliver reliable, production-ready analytics solutions. • Develop, optimize, and maintain SQL queries, notebooks, and scripts for data ingestion, transformation, and processing. • Ensure data accuracy, consistency, and integrity through validation, monitoring, and cleansing processes. • Create and maintain clear documentation for data pipelines, data models, and analytics solutions. • Monitor, troubleshoot, and optimize data pipelines and workloads to ensure performance, reliability, and scalability. • Stay current with industry trends, including AI-driven analytics, semantic modeling, and emerging data engineering best practices. Preferred Experience • Hands-on experience designing, implementing, and operating solutions in Databricks. • Strong understanding of ETL/ELT architectures, data ingestion patterns, and data pipeline orchestration. • Proficiency in Python and/or Spark for large-scale data processing. • Experience designing and implementing dimensional data models in lakehouse or modern data platform environments. • Familiarity with AI-driven analytics platforms, semantic modeling concepts, and exposure to NLP techniques. • Experience working in SAFe Agile or other scaled Agile frameworks. • Solid understanding of data governance, security, and compliance best practices in global, multi-provider data environments. Academic Credentials • Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field preferred. • Master’s degree is a plus. • Databricks and Azure certifications strongly preferred.