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The Ministry of Finance is responsible for the Government Procurement (GP) policies, which govern how government agencies conduct their procurement. With evolving needs of our public officers and changing procurement…
Merkle España, parte del grupo dentsu, busca profesionales para diseñar e implementar arquitecturas de soluciones en plataformas Cloud y mantener procesos ETL. Consulte la descripción del puesto a continuación. Si…
The Senior Data Engineer will lead a team in developing scalable data pipelines, managing data warehouses, and building data APIs using cloud platforms like GCP, AWS, or Azure. The role involves technical leadership, stakeholder management, and implementing data governance and transformation logic for AI-driven projects.
Develops full-stack Java applications (backend with Spring Boot, frontend with AngularJS/React.js) for fintech solutions, collaborating with business teams to deliver scalable, high-quality software in an Agile environment.
Hands-on Senior Data Architect leading large-scale migration of legacy data warehouses to a Databricks lakehouse on AWS for clinical and non-clinical data, combining 70% coding/building with 30% strategy at Eli Lilly in Bangalore.
Design and build a Databricks lakehouse to modernize legacy clinical and non-clinical data platforms, writing PySpark pipelines and setting governance standards for AI-ready, audit-compliant data products.
Builds ML models and runs experiments to optimize Stripe’s Link checkout, local payment methods, and consumer features, using SQL, Python, and causal inference.
4-month co-op ML Software Engineer at RBC Borealis, building ML-based software solutions end-to-end—from data ETL using Hadoop/Spark to implementing ML algorithms and front-end development—within a major bank's AI innovation lab.
Co-op ML Software Engineer at RBC Borealis building end-to-end machine learning software solutions—from data pre-processing and algorithm implementation to front-end development—using Python/C++/Java and distributed frameworks like Hadoop and Spark.
Builds and refines fraud detection models (account takeover, card fraud, merchant loss) for Stripe’s global payments platform, collaborating with engineering and risk teams to deploy solutions and drive financial integrity.
The Trading & Execution Services group within Capital Markets is seeking a strong Java developer for the Program Trading team. We are building a world-wise data organization that leverages artificial intelligence…
Builds and optimizes scalable big data platforms, focusing on distributed systems, real-time/batch pipelines, and metadata-driven tooling to accelerate data insights for analysts and scientists.
Senior Data Engineer in Amsterdam focusing on designing and operating high-quality data pipelines on a Big Data Platform, collaborating with stakeholders, and championing data best practices. Core technologies include Python, PySpark, Airflow, Hadoop, Spark, Kafka, and SQL.
Build and maintain scalable ELT data pipelines using Python, PySpark, Airflow, Hadoop, and Spark for a Big Data Platform.
Leads AI data engineering and solutioning for Singapore’s Home Team, designing scalable data pipelines, ensuring governance, and optimizing AI model inputs while driving innovation in cloud/data technologies.
Data Engineer designing, building and maintaining scalable data pipelines, data warehouses and cloud-based data platforms on AWS using SQL, Oracle PL/SQL and Python to support analytics and business decision-making.
Backend engineering intern on Shopee's Data Infrastructure team, building and maintaining big data platform products (DataMap, Scheduler, Dashboard) using Java/Python/Go, MySQL, Redis, and Kafka.
The Senior Data Engineering Lead will design and implement scalable data architectures and lead engineering projects using SQL, Spark, and cloud platforms like Azure or AWS. This role focuses on driving enterprise analytics and AI solutions through technical leadership and team collaboration.
Python backend developer for an ad tech company's flagship Ad Suite product, building and maintaining scalable cloud applications using Python and AWS services (Lambda, S3, DynamoDB, etc.) in a microservices architecture.
Design, develop, and optimize enterprise-scale data solutions on Cloudera CDP and Hadoop, building ETL pipelines with Spark, PySpark, NiFi, Sqoop, SQL, Python, and shell scripting in a Linux environment.
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