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Data Engineer building and maintaining real-time and batch data pipelines for financial analytics and payments within an iGaming company's fintech ecosystem, using SQL, ETL/ELT workflows, and streaming platforms like Kafka.
The AI Platform Engineer will build and maintain production infrastructure for AI models, focusing on deployment, monitoring, and automation within media workflows. The role utilizes MLOps practices, Python, and cloud technologies to ensure reliable, scalable AI service delivery.
This role involves building and scaling a strategic data platform using Python and AWS serverless technologies to support enterprise data integration and pipelines. The engineer will design backend services and data processing frameworks while collaborating with cross-functional teams to deliver trusted data products.
Where Ambition Meets Innovation Build a career that matches all your initiative with an impressive dose of innovation. From cutting-edge resources and a collaborative environment to the freedom to make an impact and…
Data Engineer building scalable data pipelines, ETL/ELT processes, and cloud-based data architectures (Data Warehouse, Data Lake, Lakehouse) on AWS using SQL, Python/Scala, Spark, Airflow/dbt.
Builds and maintains Java-based middleware systems for Apple’s global sales, operations, and supply chain infrastructure, ensuring seamless connectivity between sales platforms and operational systems at massive scale.
Staff Data Engineer designing and building data pipelines and platform infrastructure using Spark, Kafka, Iceberg, and Airflow, with focus on data quality, governance, and AI-assisted development workflows.
Senior Developer in Data Engineering role focusing on data stack modernization, migrating from traditional ETL tools to cloud-native ELT stack using AWS, Python, Airflow, DBT, and Snowflake. Responsible for data modeling, data quality, and building scalable data pipelines.
Senior Data Engineer on a 6-month hybrid contract modernizing the data stack, migrating from ETL tools to a cloud-native ELT pipeline on AWS using Python, Airflow, DBT, and Snowflake.
Designs and maintains AWS-based cloud solutions for Macquarie’s treasury and financial risk platforms, focusing on automation, CI/CD, and production reliability with tools like EKS, SSIS, and PowerShell.
Senior Data & AI Platform Engineer consultant at OCTO, advising and delivering data transformation solutions for clients using SQL, Python, low-code data tools (Dataiku, Alteryx, Snowflake, Databricks), and one of GCP, AWS, or Azure.
Designs and maintains AI/ML platform infrastructure (multi-cloud, CI/CD, IaC) to empower data scientists and engineers, enabling scalable AI/GenAI solutions for developers.
Designs and maintains scalable, reliable data pipelines while improving the data platform’s quality and performance using Databricks, PySpark, and Airflow.
Designs, automates, and industrializes data pipelines on GCP for financial clients, focusing on Spark/Kafka workflows, GKE orchestration, and BigQuery storage. Ensures scalability, data quality, and CI/CD integration in a cloud-first banking environment.
Senior Data Engineer designing and optimizing large-scale data pipelines on an AWS Lakehouse architecture using DBT, Spark, Iceberg, and Airflow, with IaC via Terraform and containerized deployments.
Middle AI Engineer at MTS Web Services (Finance Block) building and maintaining ML/DL/LLM infrastructure, fine-tuning models, developing RAG search and document recognition systems, and creating production data pipelines using Python, PySpark, Airflow, and vector databases.
Data Architect/Engineer responsible for designing graph-RAG platform data structures, building ETL/ingestion pipelines from enterprise sources like SharePoint, and maintaining a Neo4j knowledge graph using Python and Postgres/Supabase.
Design and build data pipelines, quality frameworks, and tooling that turn multi-modal surgical robotics data into research-ready datasets for AI/ML teams, using Python, SQL, and distributed processing frameworks like Spark and Airflow.
Onsite ML engineer in Springfield, VA designing, building, and maintaining ML systems (predictive models, recommendation engines, anomaly detection) using Python, Kubernetes, PyTorch/TensorFlow, and MLOps tooling for a national security contractor.
Builds and maintains the AI and data platform that powers Afresh's grocery-focused products, focusing on retrieval, agent systems, and evaluation infrastructure for LLMs.
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