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Builds cloud-based analytics pipelines and dashboards to extract business insights from retail data using data science and visualization tools.
Build cloud-based analytics and predictive models to turn retail data into business insights using Python, cloud data warehouses, and visualization tools.
Build and maintain Python backend services and data pipelines for a large-scale cloud data warehouse, using AWS and FastAPI/Flask while learning DevOps and AI-assisted development.
Maintains and secures SQL Server, Oracle, MySQL, PostgreSQL and cloud databases, tuning performance, enforcing backups, and troubleshooting issues for a large leisure and hospitality group.
Designs and maintains MongoDB-based data pipelines and warehouses for banking systems, implementing ETL/ELT to ensure secure, scalable financial data management.
Lead the design and optimization of Tune Protect’s data ecosystem, building scalable ETL pipelines with SSIS/Airflow and modernizing the data warehouse to support analytics and AI initiatives.
Build and deploy ML systems and AI software for clients using LLMOps, deep learning, and predictive algorithms on Azure.
Designs and maintains MongoDB databases and ETL pipelines for banking systems, ensuring secure, scalable data management for financial applications.
Analyze data to extract insights, automate workflows, and support decision-making for sales, marketing, and operations using SQL, R, and statistical modeling.
Maintain and optimize Python-based web scraping pipelines, ensure data quality for a Datalake, and troubleshoot errors in ETL workflows on Azure.
Designs and builds scalable data pipelines and modern data warehouses using Microsoft Fabric, Azure, and Databricks to enable analytics and reporting.
Build and maintain R&D analytics models and reporting in Pigment to help engineering teams ship faster and make data-driven decisions using SQL, dbt, and BI tools.
Data Engineer building modern data pipelines and warehouses using Microsoft Fabric and Azure for enterprise clients, with a focus on cloud-based AI/ML solutions and ETL/ELT workflows.
Designs and builds end-to-end data pipelines on Azure Synapse and Data Factory, modeling relational/ dimensional data in T-SQL and PySpark to deliver governed analytics platforms for clients in industrial, energy, consumer and public sectors.
Data Engineer leads client data migrations, mapping legacy systems to new databases using SQL, Python, and data warehousing skills while coordinating with clients and analysts.
Builds and maintains ETL pipelines and data warehouses using Python and SQL, deploys with CI/CD tools like GitLab/GitHub.
Designs and builds cloud-native data pipelines, ELT workflows, and data models for a data lake/warehouse using Python, Java, Spark, and cloud platforms like GCP or Microsoft Fabric.
Build and maintain the Agentic Data Plane, a governed interface for data and AI tools on GCP using Python, ensuring security, observability, and integration with data warehouse and metadata systems.
Builds and maintains the data warehouse and semantic layer for a fintech domain, modeling data for AI agents and business stakeholders using Domain-Driven Design.
Designs and builds data pipelines and warehouses for clients using Hadoop, Snowflake, Kafka, Spark, and Python/Java.
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