cloud, preferably AWS, is preferred. Extensive background in software architecture and solution design, with deep expertise in microservices, distributed systems, and cloud-native architectures. Advanced proficiency in Python and Apache Spark, with a strong focus on ETL data processing and scalable data engineering workflows. In-depth technical knowledge of AWS data services, with hands-on experience implementing data pipelines More ❯
techniques and tools Strong hands-on experience with cloud data platforms, specifically Google Cloud Platform - BigQuery Experience with leading ETL/ELT tools and data pipeline orchestration (e.g., Dataflow, Apache Airflow, Talend, Informatica) Advanced SQL skills and deep knowledge of various database technologies (relational, columnar, NoSQL) Practical experience in establishing data governance frameworks, data quality initiatives, and Master Data More ❯
AWS services such as S3, Glue, Lambda, Redshift, EMR, Kinesis, and morecovering data pipelines, warehousing, and lakehouse architectures. Drive the migration of legacy data workflows to Lakehouse architectures, leveraging Apache Iceberg to enable unified analytics and scalable data management. Operate as a subject matter expert across multiple data projects, providing strategic guidance on best practices in design, development, and … in designing and implementing scalable data engineering solutions. Bring extensive experience in software architecture and solution design, ensuring robust and future-proof systems. Hold specialised proficiency in Python and Apache Spark, enabling efficient processing of large-scale data workloads. Demonstrate the ability to set technical direction, uphold high standards for code quality, and optimise performance in data-intensive environments. … of continuous learning and innovation. Extensive background in software architecture and solution design, with deep expertise in microservices, distributed systems, and cloud-native architectures. Advanced proficiency in Python and Apache Spark, with a strong focus on ETL data processing and scalable data engineering workflows. In-depth technical knowledge of AWS data services, with hands-on experience implementing data pipelines More ❯
