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Build and maintain Power BI dashboards, Azure data pipelines, and cloud analytics solutions using SQL, Python, and Microsoft Fabric to deliver business insights.
Builds and maintains scalable GCP data pipelines and cloud-native solutions for enterprise analytics and AI, using BigQuery, Dataflow, and Python.
Lead a team to design, build, and maintain scalable data pipelines and analytics platforms using Azure Data Factory, Databricks, SQL Server, and Python for a global financial markets infrastructure company.
Designs, codes, and enhances custom software solutions using modern frameworks and agile practices, with a focus on data engineering and scalable systems.
Lead the design and implementation of Microsoft Fabric-based data pipelines and governance for Lilly’s Integrated Risk Management program, integrating risk platforms like ServiceNow GRC and SAP to deliver real-time, AI-ready risk datasets for analytics and decision-making.
Designs and maintains the data infrastructure for Lilly’s risk management program using Microsoft Fabric, integrating systems like ServiceNow GRC and SAP to deliver accurate, real-time risk intelligence for enterprise decision-making.
Design and build enterprise-scale data pipelines and cloud architectures on AWS, Databricks, Snowflake, and PySpark, while enabling AI-ready data platforms and leading cross-functional teams.
Designs, implements, and maintains databases using Databricks, SQL, and Python to build scalable data pipelines and ensure data integrity for enterprise clients.
Principal engineer designs and builds a secure, governed Azure/SAP data platform (Microsoft Fabric, OneLake, SAP BDC) to centralize analytics, reporting, and AI across a chemicals manufacturer.
Build and optimize ETL pipelines in Microsoft Fabric using Python, PySpark, and SQL to move and transform data for analytics and reporting, while collaborating with global teams.
Designs, builds, and maintains scalable data pipelines on Azure using Databricks, PySpark, and Python to process and deliver data for business needs.
Designs and evaluates AI-driven data solutions for Sales and Marketing at Thermo Fisher Scientific, focusing on LLM agents, data readiness, and analytics using Python, SQL, and cloud platforms.
Senior Data Scientist building and deploying AI models for industrial workflows, using Python, Databricks, and Azure AI to analyze complex datasets and improve business processes.
Senior Data Engineer builds and maintains large-scale data platforms and pipelines for a global bank, using Spark, Kafka, Iceberg, and cloud-native tools to deliver trusted, AI-ready data assets.
Data Engineer builds and runs pipelines to migrate legacy systems into a new target platform using Azure/Fabric tooling, validates data, and supports CI/CD.
Lead the development of AI/ML models for industrial equipment reliability, predictive maintenance, and failure forecasting using sensor data and deep learning, while collaborating with engineering teams to deploy production-ready solutions.
Designs and oversees large-scale data platforms and lakehouse architectures for Chevron, focusing on Azure Databricks, PySpark, and cloud data pipelines to support energy sector operations.
Builds and maintains secure, scalable data pipelines and analytics platforms for a financial regulatory agency using AWS, Databricks, and PySpark.
Build and deploy machine learning models to automate forecasting and scenario simulation for sales, finance, and commercial teams using Databricks, Azure ML Studio, and Python.
Build and ship an agentic AI platform using LLMs, RAG, and multi-agent orchestration on Azure, while mentoring engineers and setting GenAI technical direction.
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