Seeking a skilled Databricks Developer to architect, build, and manage robust data pipelines and analytics solutions. This role requires deep expertise in Apache Spark, Python, SQL, and cloud data engineering to support critical enterprise data integration and analytics initiatives.

This position is integral to developing and maintaining scalable data infrastructure, ensuring efficient data processing and insightful analytics capabilities.

Join a dynamic team focused on leveraging cutting-edge data technologies to drive business value and innovation through data.

Design, develop, and maintain scalable ETL/ELT pipelines using Databricks, leveraging Apache Spark (PySpark) for data processing.

Build and optimize both batch and streaming data pipelines, integrating data from diverse sources like databases, APIs, and cloud storage.

Implement comprehensive data transformation, cleansing, and validation processes. Develop Delta Lake tables and optimize storage with partitioning and Z-Ordering.

Create reusable Databricks notebooks, workflows, and jobs. Monitor and resolve pipeline issues, collaborating closely with stakeholders to meet data requirements. Adhere to coding standards and best practices.

Requires strong experience with Databricks and expertise in Apache Spark/PySpark. Proficiency in Python and strong SQL skills are essential.

Must have practical experience with ETL/ELT development, Delta Lake, and a solid understanding of data warehousing concepts. Familiarity with Git and version control is mandatory.

Ideal candidates will possess cloud platform experience (Azure, AWS, or GCP) and knowledge of streaming technologies like Spark Structured Streaming. Experience with orchestration tools such as Airflow is beneficial.