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Lead a team of data engineers to build scalable data pipelines and cloud infrastructure (AWS/GCP/Azure) using Spark, Kafka, and Terraform, while collaborating with data scientists to industrialize models.
Build and maintain scalable ETL/ELT pipelines on Google Cloud Platform, optimize BigQuery warehouses, and automate data workflows with Python, SQL, and Terraform for real-time analytics and business insights.
Build and maintain data pipelines, cloud infrastructure, and support data scientists in industrializing their models using technologies like Spark, Kafka, and Snowflake.
Lead a backend and data engineering team to build a zero-hallucination AI platform using Python, Apache Beam, FastAPI, and Temporal on Google Cloud Spanner and graph databases.
Design and build scalable data pipelines and cloud-based data platforms for clients, using tools like Terraform, Spark, Kafka, and Snowflake.
Build and scale backend systems managing global advertiser budgets using C# and Python with big data stacks like Hadoop, Flink, and Spark.
Designs and maintains scalable data pipelines using Spark, Kafka, and Flink, deploys AI-ready cloud architectures on AWS/GCP, and enables GenAI model integration.
Build and maintain cloud-based data pipelines and infrastructure for clients, using Spark, Kafka, and cloud tools to support ML and AI projects.
Build and deploy scalable data pipelines, cloud infrastructure, and full-stack apps that expose AI models and datasets for analysts and scientists.
Teach data engineering fundamentals to adult learners, guiding them through Python, SQL, ETL pipelines, and big-data architectures to prepare them for industry roles.
Designs and maintains scalable data pipelines and infrastructure using Python, SQL, Spark, and cloud platforms to enable analytics and AI workloads.
Senior engineer builds and runs a cloud-based big-data platform on AWS, using Cloudera services, Kafka, Flink, NiFi, and Terraform to keep pipelines fast and reliable.
Build and maintain distributed Java services using Kafka and event-driven architectures, deploy on Kubernetes, and mentor peers in a hybrid London role.
Build low-latency Java/Spring Boot microservices and event-driven pipelines (Kafka, Flink) to power real-time personalization across Tesco’s web, mobile, and in-store channels.
Staff Backend Engineer to lead Depop’s data platform, building scalable pipelines, data lake, governance, and real-time analytics using Python/Scala, Spark, Kafka, and cloud platforms.
Senior Backend Engineer builds low-latency systems that process blockchain data and detect real-time threats for wallets, exchanges, and fintech platforms.
Build and maintain a real-time liability and risk platform for a sportsbook, using Java and Flink to process bets and deliver live exposure insights.
Build and maintain scalable data pipelines and analytics for cybersecurity at a global bank, using Python, SQL, Spark, Kafka, and cloud platforms.
Build and maintain distributed observability services in Java, ingesting and processing high-volume data with Kafka and Kubernetes to power real-time monitoring for global financial institutions.
Build and maintain Tripadvisor’s petabyte-scale data pipelines and platforms using Java, Python, Spark, Flink, and Snowflake to power analytics, ML, and GenAI across the travel giant’s global brands.
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