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Build and maintain scalable data pipelines and Databricks solutions to transform scientific datasets for regulatory compliance and product safety in agriculture.
Senior Data Engineer to modernize analytics infrastructure by building an Azure-based data platform with DevOps, automated pipelines, and scalable architecture using Python, SQL, and Azure services.
Lead a 5–7 person team to design, build, and scale low-latency data infrastructure for a high-frequency trading firm, using Python, Java, Kafka, and Delta Lake/Iceberg.
Demonstrate Databricks’ data/AI platform to UK customers, build POCs in Spark/Python/Java/Scala, and advise on big-data architectures to solve enterprise challenges.
Senior Data Engineer to modernize analytics infrastructure by building an automated, Azure-based data platform with DevOps, pipelines, and governance for real-time insights.
Architect and lead Faire’s ML platform, setting standards for MLOps, feature management, and scalable ML workflows using Databricks, Spark, and MLflow to empower data scientists and retailers.
Design and harden enterprise-scale Databricks data platforms for clients, building guardrails and automation so teams can safely build on the platform using PySpark, Structured Streaming, and AWS-native patterns.
Job Family: Data Science & Analysis Travel Required: Up to 10% Clearance Required: Ability to Obtain Public Trust What You Will Do: Design, build, and optimize scalable, production-grade data ingestion, transformation,…
Designs and maintains scalable data pipelines and analytics solutions using Databricks, SQL, and Python to deliver trusted data insights for business decisions.
Maintains and optimizes enterprise data platforms (MSSQL, Microsoft Fabric) and data pipelines, ensuring reliability and performance while supporting migrations to modern cloud solutions.
Build and scale Trino/Iceberg-based data pipelines for Wise’s finance team, transforming raw financial events into audit-ready reports using Medallion Architecture and Kafka.
Lead hands-on data engineering for clients in retail, media, and finance, building cloud pipelines and models on Azure, Databricks, and Fabric to power AI solutions and analytics.
Build and govern an AI-native data platform for the world’s largest jewellery company, using Unity Catalog, Confluent Schema Registry, and OpenMetadata to automate governance, metadata, and access at scale.
Build and optimize cloud data pipelines and lake house architectures for a global iGaming provider, migrating on-prem systems to AWS/Azure and implementing Kafka-driven streaming pipelines.
Lead a team building Grab’s Customer Data Platform, enabling real-time personalization, ML, and ad targeting by processing billions of events per hour with Python, Go, and distributed systems.
Leads a team to build and maintain Prudential Malaysia’s data lake and enterprise data model on Azure, enabling analytics, AI, and regulatory reporting while ensuring governance and compliance.
Build and productionise Databricks lakehouse data products for a large financial services client, using Spark, Delta Lake, and Azure/Google Cloud to deliver governed datasets and self-service analytics.
Builds scalable cloud-native microservices in Java/Python, leveraging AI to automate workflows and boost engineering productivity for enterprise clients.
Builds scalable Java/Python microservices on Azure while using AI tools to automate coding, testing, and DevOps, improving engineering productivity.
BUSINESS UNIT DESCRIPTION: Enterprise Payments Technology (EPT) is a technology function within CIBC Enterprise Technology, supporting the applications and platforms that enable wire payment processing services across…
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