Job Details

Senior Data Engineer for a European bank. Working with Data Lakehouse on AWS, ETL using Python and Spark. Requires experience in Data Engineering, SQL, AWS (EMR, Glue, Athena, S3), Python, Spark, and fluent English.

Designing and developing a modern data platform for a major European bank. You will be involved in creating scalable Data Lakehouse solutions in the AWS cloud, ensuring efficient processing of vast amounts of information and building reliable pipelines. Technology Stack: Processing: Apache Spark (large-scale data processing). Cloud (AWS): EMR, Glue, Athena, S3-based data lakes. Languages: Python (ETL, automation), expert SQL. Architecture: Data Lakehouse, Cloud Object Storage, Open Table Formats. Modeling: Analytical and dimensional data modeling. Responsibilities: — Designing, implementing, and supporting fault-tolerant data pipelines. — Developing ETL processes using Python and Spark for large-scale processing. — Working with modern Data Platform concepts (distributed computing, Data Lakehouse). — Ensuring the reliability and scalability of the data architecture in an enterprise environment. — Active collaboration with an international team in English.

Requirements (Must-have): — Deep practical experience in Data Engineering within large corporate environments. — Expert-level SQL proficiency and understanding of data modeling principles. — Strong experience with AWS data services (EMR, Glue, Athena, S3). — Practical development skills in Python and Apache Spark. — Systems thinking and the ability to solve complex problems at the intersection of infrastructure and data. — Fluent English (written and spoken) for effective communication.