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Builds and maintains big data pipelines using Cloudera CDP, Spark, Hive, and Hadoop to support analytics and production systems.
Senior Data Engineer builds and maintains Azure-based data pipelines, warehouses, and lakehouses to power analytics and AI workloads using PySpark, Azure Synapse, and ADF.
Designs and optimizes cloud-based ETL/ELT pipelines using Azure Data Services, builds scalable data warehouses, and improves data quality for analytics teams.
Build and own the cloud infrastructure and MLOps platform for a regulated fintech firm’s AI trading systems on AWS, including Kubernetes, CI/CD, and model deployment pipelines.
Build and optimize CI/CD pipelines for Oracle databases and PySpark deployments using OpenShift, Jenkins, and Docker to automate data engineering workflows.
Build and maintain Node.js/Express backends and Python FastAPI services, using MongoDB and Azure Databricks to create ETL pipelines and automation.
Designs and builds data pipelines on Google Cloud Platform, focusing on BigQuery, Dataflow, and Pub/Sub, while integrating agentic AI components using Python and MCP servers.
Build and maintain ETL pipelines and data models using Python, SQL, PySpark, and AWS services for store operations and sales analytics.
Build and optimize cloud-native data pipelines on GCP to power AI, ML, and analytics products used by millions of banking customers.
Build and maintain scalable data pipelines for Plenitude’s EV-charging network, using Python, PySpark, AWS, and Databricks to feed analytics and operations.
Design and build end-to-end data pipelines on Azure Synapse and Data Factory, modeling relational and dimensional data in T-SQL/PySpark to deliver modern, scalable analytics platforms for enterprise clients.
Builds and maintains scalable data pipelines on Databricks and Azure Synapse using PySpark, Python, and SQL to ensure reliable data solutions.
Lead a team building scalable AI and data platforms for enterprise clients, designing cloud-native architectures, MLOps pipelines, and generative-AI solutions using Python, Spark, and cloud stacks like AWS/Azure.
Leads AI agent design, testing, and deployment for a financial group, focusing on robust, safe workflows and LLM evaluation in Python and Azure.
Designs and builds big-data pipelines and reports using Cloudera, PySpark, SQL, and BI tools to deliver clean, accessible datasets and dashboards.
Build and maintain AI-powered document parsing pipelines, OCR/VLM systems, and RAG knowledge bases on Azure to extract and structure data from PDFs, images, and videos for GenAI applications.
Build and maintain scalable data pipelines and backend services for wealth-management analytics using Python, Spark, SQL, and cloud platforms like Azure.
Design and build data pipelines, ETL workflows, and dashboards using Python, PySpark, SQL, and tools like Cloudera and Tableau to deliver analytics solutions.
Senior data engineer builds and optimizes reporting pipelines, ETL workflows, and dashboards for a government authority using Python, PySpark, SQL, and Cloudera tools.
Lead data engineering teams to build and migrate data lakes, warehouses, and lakehouses using PySpark, Python, and cloud platforms like AWS/Azure/GCP.
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