4 of 4 Data Pipeline Jobs in Midlothian

now to be part of our award-winning team at Sparta Global. About this role You'll become versatile in a wide array of tools across topics covering data focused coding, data visualisation, Cloud Services, Big Data and Machine learning. You will be equipped to work within a variety of roles including but not … limited to; Data Engineer, Data Analyst, Data Scientist, Information Engineer. You'll be designing, building, maintaining, and troubleshooting the data pipelines that enable organizations to store, process, and analyse their data, and ensuring the data is reliable through testing and debugging. Looking for efficiencies and optimising the data pipelines for scalability and performance will be a focus. You'll be handling and working with large sets of structured and unstructured data and will be responsible for ensuring that the data is organized and available for further analysis and investigation. Working with others is key, you could be working with other engineers, developers More ❯

using FastAPI and integrate with external systems. Deploy scalable AI systems using AWS (Lambda, S3, SQS, EKS/ECS), CDK , and modern DevOps practices. Collaborate on infrastructure and data pipelines using SQLAlchemy, Boto3, Pandas, and Airflow . Contribute to real-time AI services , model versioning, and advanced fine-tuning (LoRA, QLoRA, etc.). AI Engineer requirements: Solid Python More ❯

OCR Leveraging frameworks like Hugging Face Transformers , PyTorch , YOLO , OpenCV , and Pillow Designing and deploying AI services via FastAPI , AWS Lambda , EKS/ECS , and S3 Creating scalable data pipelines with Pandas , NumPy , SQLAlchemy , and Airflow Supporting real-time model inference, edge deployments, and API integrations Working closely with a technical lead in a service-based and serverless More ❯

services such as Logic Apps, Function Apps, Service Bus, Event Grid, and Event Hub. Collaborate with architects to define patterns for event-driven and API-based integrations. Develop data pipelines and orchestrations using Azure Data Factory and Abinitio to support batch and near-Real Time data integration scenarios. Implement automated deployment and testing of More ❯