Databricks Engineer

Databricks Engineer

The Person

You are a detail-oriented and analytical problem solver who enjoys tackling complex data challenges. You communicate clearly and collaborate effectively with cross-functional teams to deliver meaningful, data-driven solutions. You are adaptable, service oriented, curious, and passionate about using modern data technologies to unlock insights. Highly organized and proactive, you can manage multiple priorities while maintaining a strong focus on quality, scalability, and innovation.

Key Responsibilities

• Implement and optimize data models and structures within Databricks to support efficient querying, analytics, and reporting.
• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows, with a strong emphasis on dimensional data modeling and data quality.
• Partner with engineering teams and business stakeholders to gather requirements and deliver reliable 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 data cleansing processes.
• Create and maintain comprehensive documentation for data pipelines, models, and analytics solutions.
• Monitor, troubleshoot, and optimize data pipelines and analytics workloads to ensure performance and reliability.
• Stay current with industry trends, including AI-driven analytics tools, semantic modeling, and emerging data engineering best practices.

Preferred Experience

• Hands-on experience implementing and operating solutions in Databricks.
• Strong understanding of ETL/ELT architectures and data ingestion patterns.
• Proficiency in Python and/or Spark for large-scale data processing.
• Experience designing and implementing dimensional data models in data lakehouse environments.
• Familiarity with AI-driven analytics platforms, semantic modeling concepts, and NLP techniques.
• Experience working in SAFe Agile or other scaled Agile environments.
• Solid understanding of data governance, security, and compliance best practices in global environments with numerous data providers and consumers.

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.