Join our team as a Data Engineer and contribute to building robust data solutions. This role involves designing, developing, and maintaining data generation, collection, and processing systems. You will be instrumental in creating efficient data pipelines, ensuring data integrity, and implementing ETL processes for seamless data migration across various platforms.

As a Data Platform Engineer, you will collaborate with Integration and Data Architects to shape the data platform blueprint and design, ensuring cohesive system integration and data model alignment. Your expertise will be crucial in defining and refining the core components of our data platform.

Design, build, and optimize scalable data pipelines for large-scale data processing within the data engineering team. Develop and implement ETL/ELT processes using PySpark and Spark to manage data movement and transformation from diverse sources. Assist in deploying solutions on major cloud platforms like AWS, Azure, or GCP. Support the maintenance of Big Data frameworks and data lakes for structured and unstructured data. Ensure data accuracy and availability by collaborating with data scientists, analysts, and other engineers. Implement secure and efficient data ingestion strategies for cross-storage solutions. Work with real-time streaming and batch processing for high-volume data. Develop reusable code for ETL operations and contribute to performance tuning of Spark jobs and pipelines.

A minimum of 3 years of experience in data engineering is required. Proficiency in Databricks Unified Data Analytics Platform is a must. Experience with cloud platforms such as AWS, Azure, or GCP is essential. Strong skills in PySpark, Spark, or similar frameworks for scalable data pipeline development are needed. Understanding of Big Data architectures, data storage, and processing concepts is crucial. Familiarity with cloud-native data storage solutions and data orchestration tools is expected. Excellent coding skills in Python and a good understanding of SQL and database technologies are required. Strong troubleshooting, debugging, and performance optimization skills are necessary. A background of 15 years of full-time education is mandatory.