About GFT GFT Technologies is driving the digital transformation of the world’s leading financial institutions. Other sectors, such as industry and insurance, also leverage GFT’s strong consulting and implementation skills across all aspects of pioneering technologies, such as cloud engineering, artificial intelligence, the Internet of Things for Industry 4.0, and blockchain. With its in-depth technological expertise, strong partnerships and scalable IT solutions, GFT increases productivity in software development. This provides clients with faster access to new IT applications and innovative business models, while also reducing risk. We’ve been a pioneer of near-shore delivery since 2001 and now offer an international team spanning 16 countries with a global workforce of over 9,000 people around the world. GFT is recognised by industry analysts, such as Everest Group, as a leader amongst the global mid-sized Service Integrators and ranked in the Top 20 leading global Service Integrators in many of the exponential technologies such as Open Banking, Blockchain, Digital Banking, and Apps Services. Role SummaryAs a Senior/Lead Data Engineer at GFT, you will be responsible for managing, designing, and enhancing data systems and workflows that drive key business decisions. The role is focused 75% on data engineering, involving the construction and optimization of data pipelines and architectures, and 25% on supporting data science initiatives through collaboration with data science teams for machine learning workflows and advanced analytics. You will leverage technologies like Python, Airflow, Kubernetes, and AWS to deliver high-quality data solutions. Key Activities Architect, develop, and maintain scalable data infrastructure, including data lakes, pipelines, and metadata repositories, ensuring the timely and accurate delivery of data to stakeholdersWork closely with data scientists to build and support data models, integrate data sources, and support machine learning workflows and experimentation environmentsDevelop and optimize large-scale, batch, and real-time data processing systems to enhance operational efficiency and meet business objectivesLeverage Python, Apache Airflow, and AWS services to automate data workflows and processes, ensuring efficient scheduling and monitoringUtilize AWS services such as S3, Glue, EC2, and Lambda to manage data storage and compute resources, ensuring high performance, scalability, and cost-efficiencyImplement robust testing and validation procedures to ensure the reliability, accuracy, and security of data processing workflowsStay informed of industry best practices and emerging technologies in both data engineering and data science to propose optimizations and innovative solutions