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Build AI-powered knowledge systems and retrieval pipelines for an HCM suite, integrating LLMs, RAG, and agentic workflows in TypeScript/Node.js and Python.
Senior Data Engineer builds and maintains cloud data pipelines and warehouses using Snowflake, Airflow, and AWS to power analytics and decision-making across a large enterprise.
Builds enterprise knowledge graphs and AI solutions using Neo4j or Amazon Neptune to model complex data relationships, metadata, and lineage for analytics and generative AI.
Design and build scalable data pipelines on Azure Databricks and Microsoft Fabric, mentor junior engineers, and deliver cloud-native analytics solutions for clients across finance, government, and other sectors.
Build and govern a unified semantic data layer for finance, HR, procurement and compliance using Databricks, dbt and PySpark to power self-service analytics and AI agents.
Build and maintain a Snowflake-centric cloud data platform to power analytics and decision-making at a major airline, using Python, SQL, Airflow, and AWS.
Design and lead a modern, cloud-agnostic enterprise data ingestion framework, building scalable pipelines for batch and streaming data across multi-cloud environments.
Design and maintain scalable data pipelines and Lakehouse/Warehouse solutions using Microsoft Fabric to modernize SCC’s analytics platform and integrate clinical, finance, and operational data for trusted insights.
Analyze US healthcare claims, eligibility, and provider data using SQL and Snowflake; build data models, reports, and CI pipelines for value-based care and regulatory needs.
Build and maintain scalable data pipelines to clean, version, and serve terabytes of training data for autonomous defense ML models.
Lead a data engineering team to build and operate a secure, scalable Databricks lakehouse on Azure for banking analytics, AI, and regulatory reporting using Kafka, dbt, and Unity Catalog.
Builds and deploys production-grade AI, ML, generative AI, and computer vision systems for a hospital, integrating with EHR, imaging, and clinical workflows while ensuring safety and scalability.
Lead a team building and optimizing large-scale data pipelines, data lakes, and warehouses using Azure, Spark, Kafka, and Snowflake to power analytics and ML for Emirates’ enterprise systems.
Design and build data pipelines, warehouses, and analytics solutions for Emirates Group using Azure, Spark, Kafka, and SQL to support airline operations and reporting.
Design and maintain ETL/ELT pipelines using Informatica Cloud to integrate and transform enterprise data from diverse sources for analytics and reporting.
Designs and evaluates enterprise-scale GenAI multi-agent systems, focusing on RAG, LLM orchestration, and integration with platforms like Databricks and Mosaic AI.
Design and build secure, scalable data pipelines and infrastructure for ADAPT, a real-time energy-sector platform, using Azure services to enable live analytics and automation across maintenance and supply-chain operations.
Lead the design and implementation of enterprise data platforms, data architecture, and BI systems for a pharmaceutical company, ensuring scalable, secure, and high-performing solutions.
Lead the Group’s data governance framework, define master data standards, enforce quality rules, and partner with teams to ensure consistent, compliant data across all entities and systems.
Design and maintain enterprise data catalogs and lineage tools to ensure compliance and discoverability across data assets.
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