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Designs and builds scalable data pipelines and platforms using Microsoft Fabric, Azure Data Factory, Python, PySpark, and SQL to enable analytics and AI for enterprise clients.
Project Manager to lead a firm-wide data and lakehouse replatforming initiative, modernizing core platforms and data capabilities using open-source technologies.
Designs and maintains scalable backend services, APIs, and data pipelines for healthcare clients using Node.js, Java, Python, and AWS, focusing on integrations, security, and cloud-native architectures.
Senior Software Engineer owning performance-critical paths in a large-scale data-processing platform, profiling and optimizing with Python, C/C++/Rust, PostgreSQL, and GPU/CUDA acceleration.
Securitas Group Securitas is a world-leading safety and security solutions partner that helps make your world a safer place. By leveraging technology in partnership with our clients, we offer a broad portfolio of…
Builds and optimizes data pipelines using Databricks, PySpark/Scala, and Azure cloud services to transform and govern enterprise data in a lakehouse architecture.
Build and maintain Dremio’s core platform services—telemetry, messaging, caching, and access control—using Java, Kubernetes, and Terraform to power scalable, self-service analytics and AI for global enterprises.
Senior full-stack engineer building Java back-ends, Next.js/React portals, and Databricks lakehouse features while driving test automation and code quality for GM’s PVSQ organization.
Designs robust, scalable architectures for a regulated bank, integrating data, event processing, and AI/ML into enterprise platforms while aligning with financial-sector standards.
Build end-to-end BI solutions on Microsoft Fabric, from data ingestion to Power BI dashboards, to deliver actionable insights for global healthcare teams.
Build and optimize scalable data pipelines and governed lakehouse platforms using Databricks, Spark, and AWS to support analytics and AI in a regulated biotech environment.
Lead a team to design and deliver scalable data pipelines and platforms for analytics and AI use cases at Mastercard, using SQL, Python, and Databricks.
Design and build scalable cloud-native data pipelines and platforms (batch/streaming) using Python, Spark, Kafka, and cloud data warehouses to power analytics and ML across global telco markets.
Lead a team of 8–15 engineers to design, build, and optimize cloud-based data pipelines and lakehouse architectures using Python, PySpark, Databricks, and cloud platforms like Azure/AWS/GCP.
Designs and maintains scalable data pipelines and platforms to power analytics and reporting across a global healthcare company using cloud technologies and ETL/ELT processes.
Lead a team of data engineers building and operating the data platforms that power Grata’s private-market dealmaking platform, using Python, SQL, Spark/Databricks, and AWS.
Senior AWS data engineer building scalable healthcare data platforms using EMR, Glue, S3, and Redshift to power global health informatics solutions.
Design and build AI-ready data pipelines and products that power retrieval-augmented AI systems, ensuring data quality, governance, and secure access for AI models.
Build and maintain Greystar’s Databricks-native data platform on Azure, administering Unity Catalog, optimizing Spark jobs, and enforcing medallion architecture standards for reliable, cost-efficient enterprise analytics.
Build and optimize Microsoft Fabric lakehouse pipelines and PySpark transformations, then deliver Power BI reports for a US renal-care analytics platform.
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