This role as a Data Platform Engineer involves contributing to the data platform's blueprint and design, ensuring the seamless integration of its components. You will collaborate closely with Integration Architects and Data Architects to guarantee a cohesive connection between various systems and data models, playing a pivotal part in shaping the platform's architecture.

We are seeking a professional who can assist with the data platform blueprint and design, encompassing relevant data platform components. This role requires collaboration with Integration Architects and Data Architects to ensure cohesive integration between systems and data models, focusing on the Databricks Unified Data Analytics Platform.

As a Data Platform Engineer, you will be instrumental in building and optimizing scalable data pipelines for extensive data processing within the data engineering team. This includes developing and implementing robust ETL/ELT processes using PySpark and Spark for data movement and transformation from diverse sources.

You will also assist in designing and deploying solutions across major cloud platforms like AWS, Azure, or GCP, and support the development and maintenance of Big Data processing frameworks and data lakes. Collaboration with data scientists, analysts, and engineers is key to ensuring data accuracy and availability, alongside implementing efficient data ingestion strategies and working with real-time streaming and batch data pipelines. Developing reusable code for ETL operations and contributing to the performance tuning of Spark jobs are also essential duties.

This position requires a minimum of 3 years of experience, with a preferred range of 2-5 years. A strong foundation in the Databricks Unified Data Analytics Platform is essential.

Technical proficiency includes experience with AWS, Azure, or GCP for data engineering tasks, and strong skills in PySpark or Spark for building scalable data pipelines. Understanding Big Data architectures, data storage concepts, and familiarity with cloud-native data storage solutions are expected. Robust coding skills in Python, good SQL knowledge, and excellent troubleshooting abilities are also crucial for this role.