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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,…
Design and build cloud-based data analytics infrastructure using AWS, Databricks, and IDMC, focusing on healthcare data pipelines and ETL/ELT workflows.
Build and maintain scalable data pipelines on Databricks and Azure, integrating diverse sources and ensuring clean, reliable data for analytics and ML workloads.
Senior Data Engineer builds and maintains scalable pipelines and cloud data platforms (Spark, Kafka, Snowflake/BigQuery/Databricks) to power AI and analytics for a regional logistics group.
Architect and maintain scalable data pipelines and warehouses (Snowflake, Redshift, Athena) to power analytics and AI workflows, using Python, SQL, Airflow, and Kafka.
Lead a cloud-based data engineering team to build and maintain robust data pipelines, migrate legacy systems to Snowflake and AWS Glue, and ensure high-quality data flows for analytics and reporting.
Build AI-ready data pipelines and knowledge systems for an investment firm’s agentic AI, integrating structured financial data, unstructured research, and real-time feeds into vector stores, graph databases, and retrieval pipelines.
Build and maintain scalable data pipelines on Databricks and Azure, integrating diverse sources and enabling analytics and ML workloads with PySpark and Delta Lake.
Lead a data engineering team to maintain cloud data pipelines, warehouses, and lakes, migrating legacy systems to Snowflake and AWS while ensuring stability and performance.
Design and build cloud-based data analytics infrastructure using AWS, Databricks, and IDMC, migrating and modernizing healthcare data pipelines and ETL workflows.
Designs and maintains cloud-based data pipelines and warehouses using AWS, Databricks, and Informatica to support healthcare analytics and reporting.
Design and implement Neo4j graph models for banking data, apply graph algorithms to detect fraud, and build real-time investigation dashboards for AML teams.
Build and maintain scalable data systems, design ETL/ELT pipelines, and optimize data quality using AWS, Python, SQL, and Spark for analytics and ML workloads.
Design and run Databricks-based data/ML platforms on AWS for a financial-crime product, focusing on governance, security, and DevSecOps rather than Spark coding.
Builds and maintains Python microservices on AWS Lambda, designing REST APIs and integrating DynamoDB, SQS, and CloudWatch while collaborating in Agile teams.
Build and optimize scalable ETL pipelines, real-time data ingestion, and multi-tenant analytical databases to power sub-second BI dashboards and embedded analytics for a media-focused SaaS platform.
Build and automate the cloud infrastructure for a UK trading business using Terraform, AWS CDK, and GitHub Actions, ensuring reliable, secure, and observable deployments.
Build and maintain scalable data pipelines and cloud data warehouses (Snowflake/AWS Redshift/Azure Synapse) to power AI-driven healthcare analytics in Saudi Arabia, integrating HL7/FHIR clinical data.
Design and maintain scalable data pipelines and cloud data warehouses to power AI-driven healthcare solutions in Saudi Arabia, integrating clinical and claims data using HL7/FHIR standards.
Build and maintain the data pipelines and retrieval layer that power Mirai’s Generative AI products on AWS, including vector stores, embeddings, and governed datasets.
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