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Builds and maintains data pipelines, ETL workflows, and reporting dashboards for clients using Python, PySpark, SQL, and tools like Tableau and Cloudera.
Build and deploy ML models and LLM-based apps for beauty ecommerce, including recommendation engines and NLP, using PyTorch, FastAPI, and GCP VertexAI.
Build and maintain scalable data pipelines using PySpark on AWS, including ETL/ELT workflows with Glue and Step Functions, serverless automation with Lambda, and IaC with Terraform.
Lead the design and deployment of GenAI solutions for insurance, including RAG pipelines, vector databases, and LLM fine-tuning on AWS to deliver context-aware AI capabilities.
Build and maintain scalable data pipelines and ETL processes using SQL, Python, Databricks, and PySpark to deliver reliable, high-quality data solutions for analytics and reporting.
Designs and builds scalable AWS data pipelines using PySpark, AWS Glue, and serverless services to process and deliver data efficiently.
Lead a team to build and maintain scalable data infrastructure and analytics platforms using Python, Spark, and AWS, enabling investment decisions at a global sovereign wealth fund.
Build and maintain cloud data pipelines in PySpark on Databricks, transforming raw financial data into validated datasets for institutional clients.
Lead a team to design and build Microsoft BI solutions (ETL, SSAS Tabular, Power BI) for banking domains, optimizing SQL Server performance and mentoring engineers.
Build and maintain scalable data pipelines on Databricks and Azure, integrating diverse sources and ensuring clean, reliable data for analytics and ML workloads.
Designs and maintains scalable data pipelines using SQL, Python, Databricks, and PySpark to ingest, transform, and integrate data while ensuring quality and governance.
Build and optimize data pipelines and applications using Hadoop, Spark, Python, and Airflow to power Singtel’s 5G, cloud, and analytics platforms.
Build and maintain Azure-based data pipelines using PySpark, Synapse, and Azure DevOps to ingest, transform, and orchestrate data for analytics and reporting.
Design and build scalable on-premise data pipelines and lakehouse solutions using Python, PySpark, and SQL Server to power data-driven decisions across a global banking group.
Senior Data Engineer builds and maintains on-premise data pipelines and lakehouse solutions using Python, PySpark, SQL Server, and Kubernetes to enable data-driven decisions across a global banking group.
Build and maintain scalable data pipelines using Python, PySpark, and SQL to feed enterprise analytics and reporting systems.
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 and maintain scalable ETL pipelines using Talend, PySpark, and SQL to integrate data sources for analytics and ML workloads.
Build and maintain Palantir Foundry ontologies, pipelines, and operational apps to model Nscale’s AI infrastructure and business workflows, partnering directly with teams to deliver trusted data products.
Lead a small team to design, build, and scale data pipelines and platforms using Python, SQL, and cloud tools, ensuring reliable data for analytics and ML products.
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