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Build and scale real-time AI systems for crypto market intelligence, using LLMs, RAG, and streaming pipelines to turn social signals into actionable trading insights.
Builds and maintains distributed systems on AWS, automates workflows, and writes REST/SOAP services while collaborating in an Agile team.
Build and maintain ETL/ELT pipelines and data models on AWS to power network operations, migrating legacy systems to cloud-native platforms while ensuring data quality and reliability.
Build AI-powered cybersecurity tools: design LLM pipelines, retrieval systems, and MCP infrastructure to help security leaders assess risk with trustworthy, actionable insights.
Build and optimize AWS-based data pipelines and ML workflows using SageMaker, Kinesis, Glue, and Redshift, ensuring low-latency real-time and batch processing with Python and AWS services.
Build and maintain scalable data pipelines and cloud-based platforms using AWS, Python, Spark, and Databricks to power Sportsbet’s analytics and AI-driven products.
Build and maintain scalable data pipelines and cloud-based data platforms using AWS, Python, Spark, and Databricks to power Sportsbet’s analytics and AI-driven products.
Lead the design and maintenance of a data lake and warehouse, ingesting structured/unstructured data, and mentoring a team of data engineers using Azure Data Factory, Databricks, and Python.
Build and modernize payment and automation systems using C#, .NET, Angular, Azure, and AI tools in a 12-month contract role.
Build and deploy cloud-native apps using .NET, ReactJS, and Terraform on AWS/Azure, while owning CI/CD pipelines and DevOps practices for scalable enterprise solutions.
Build and maintain data pipelines and troubleshoot production issues for client projects using Python, SQL, and Spark.
Build and maintain scalable backend services using Python, AWS Lambda, and MongoDB, while contributing to Vue.js/TypeScript frontend features in a collaborative team.
Build and maintain scalable backend services for PayU’s fintech and payments platform using Node.js, TypeScript, and cloud infrastructure (AWS).
Design and implement scalable AWS data engineering solutions for enterprise customers, advising on analytics and ML architectures while managing complex cloud migrations and projects.
Build and maintain Java-based microservices and batch programs on AWS, using Spring, Hibernate, and Spring Batch to support backend APIs and scheduled data processing.
Build and maintain scalable data pipelines, ETL/ELT workflows, and cloud-based data warehouses using SQL, Python, and AWS/GCP tools to support analytics and backend services.
Build and maintain scalable data pipelines using PySpark on AWS, including ETL/ELT workflows with Glue and Step Functions, serverless automation with Lambda, and IaC with Terraform.
Build and maintain AWS-based data pipelines and warehouses using Glue, Redshift, and S3, with CI/CD and IaC for scalable ETL/ELT workflows.
Architect and build an AI-driven logistics engine for a last-mile delivery network, designing distributed systems, ML pipelines, and real-time routing logic in Python on AWS.
We are looking for an experienced Data Engineer (Cloud) to join our growing team. The ideal candidate should have hands-on expertise in designing and developing cloud-based data solutions using AWS, Databricks, Python,…
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