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About Man Group Man Group is a global alternative investment management firm focused on pursuing outperformance for sophisticated clients via our Systematic, Discretionary and Solutions offerings. Powered by talent and…
Rebuilds and operates a US sports-insurance client’s data platform, migrating from legacy ETL to Azure/Snowflake pipelines, productionizing ML scoring, and owning DevOps (IaC, CI/CD, cloud migration).
Designs and maintains scalable data pipelines and warehouses, integrating diverse sources to enable analytics and reporting using Python, SQL, and cloud tools.
Чем предстоит заниматься: проектирование, настройка и поддержка ETL/ELT пайплайнов (AirFlow/Kafka) проектирование и внедрение систем управления качеством данных настройка, поддержка и развитие каталогов данных (…
Data Engineer responsible for operating, supporting, and optimizing enterprise data platforms on Google Cloud Platform, managing ETL/ELT pipelines and ensuring data quality and security in an on-site role in Bogotá.
Builds and maintains Google Cloud infrastructure (Kubernetes/GKE, CI/CD, monitoring) for a public-sector platform, using Terraform, Helm, and Cloud-native tools to support scalable, regulated environments.
Platform DevOps engineer on a 5-month contract owning Google Cloud infrastructure for a large-scale public-sector platform, focusing on GKE, Helm, Terraform, CI/CD pipelines, and cloud-native monitoring.
Обязанности: •Разработка и поддержка BI-решений Банка (разрабатывать модули приложений согласно FSD, НФТ, требованиям производительности, архитектуры и стандартам разработки) •Исправление дефектов ПО •Разработка…
Designs and builds Databricks-based data pipelines (batch/streaming) and Lakehouse architectures using Delta Lake, PySpark, and SQL for advanced analytics and data transformation.
Data Engineer designing and maintaining ETL/ELT pipelines with SQL, Python/Scala/Java, Airflow/NiFi/Prefect, and relational/NoSQL databases on a cyberdefense project for a large defense company.
Build and own data lake/warehouse architecture, ELT pipelines, and data QA systems, integrating LLM workflows and vector databases using Python, SQL, and Apache Airflow.
The Python Developer will build and maintain scalable data pipelines and backend services for a vehicle pricing and recommendation platform. The role involves processing large datasets and delivering insights via APIs using Python, SQL, and Airflow in an Agile environment.
Build and maintain distributed, scalable backend data processing pipelines handling terabytes of satellite and external data daily for a real-time energy flows SaaS platform, using AWS, Kubernetes, Airflow, and Python.
The U.S. Pharmacopeial Convention (USP) USP is an independent scientific organization that collaborates with the world's top experts in health and science to develop quality standards for medicines, dietary…
Staff ML/AI Platform Engineer responsible for designing, building, and scaling the ML/AI platform infrastructure, including model deployment pipelines, frameworks, and tools to productionize AI/ML products at BetterHelp.
Data Engineer owning and scaling AWS-based data infrastructure for analytics and applications, building ETL pipelines, enforcing data quality, and maintaining documentation across agile squads at Singapore's Land Transport Authority.
Designs and maintains production-grade data pipelines for AI/ML and RAG systems, focusing on ingestion, transformation, and vector search infrastructure (pgvector, Pinecone). Ensures data governance, compliance, and quality for regulated sectors like healthcare and government.
Senior Data Engineer building AI-ready data pipelines, RAG/vector search infrastructure, and data governance solutions using Python, Airflow, Kafka, and vector databases like pgvector and Pinecone.
Design, deploy, and manage containerized data pipelines and data lake/lakehouse architectures using SQL Server, Python, Kubernetes, Apache Airflow, and Spark.
Freelance Azure Data Engineer building a modern cloud data platform on Microsoft Azure—designing data pipelines, warehouses, and data lakes to support reporting, analytics, and AI workloads.
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