Join our team as an Application Support Engineer, where you'll be the linchpin in identifying and resolving complex issues within critical business systems. This role is pivotal for ensuring the seamless operation of our technology infrastructure. You will act as a software detective, providing dynamic support and problem-solving across various system components.

We are particularly seeking an experienced Databricks Data Engineer with a robust background in building scalable data pipelines and managing large datasets. Your expertise in Python and SQL, combined with hands-on experience in Databricks, will be essential for translating business needs into effective technical solutions. This is an opportunity to contribute to impactful, business-driven outcomes.

Design, develop, and refine ETL pipelines and workflows leveraging Databricks, Python, and SQL. Manage extensive datasets to guarantee optimal performance, scalability, and data integrity. Transform business requirements into sophisticated data models, queries, and scripts. Implement data transformations, orchestration, and automation directly within Databricks. Collaborate closely with analysts, data scientists, and business stakeholders to deliver actionable insights. Develop dashboards and reports utilizing Power BI or similar business intelligence tools. Adhere to data governance, security protocols, and industry best practices. Create comprehensive documentation for processes, pipelines, and solutions to facilitate knowledge sharing.

A minimum of 3 years of professional experience is required, with a specific emphasis on candidates possessing 6+ years of experience in Databricks Data Engineering. Demonstrate strong proficiency in Python and SQL, backed by extensive hands-on experience. Possess deep expertise in Databricks, including data engineering, Spark functionalities, and orchestration. Proven experience in handling large datasets and optimizing system performance. Solid understanding of data warehousing concepts and ETL workflow principles. Familiarity with BI tools such as Power BI or Tableau for reporting and data visualization. Exposure to cloud platforms like Azure, AWS, or GCP, and version control systems like Git. Excellent problem-solving, communication, and collaboration skills are essential. Exposure to machine learning workflows within Databricks is considered a significant advantage.