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Design and evolve a modern data platform using Databricks to build scalable Lakehouse pipelines and real-time analytics for ML and business decision-making.
Build and optimize cloud data pipelines for analytics using Azure Data Factory, Databricks, and Power BI to enable strategic decision-making for enterprise clients.
Design and automate scalable data pipelines for a biotech company, transforming genetic-breeding research data into a high-performance lakehouse using Microsoft Fabric Data Factory.
Designs and builds Azure Databricks data pipelines and Lakehouse architectures using modern data processing tools.
Builds and maintains scalable data pipelines and lakehouse architectures to feed BI, analytics, and AI workloads using SQL, Python, and cloud platforms.
Designs and builds scalable data platforms (lakehouse, ETL/ELT pipelines) and ensures data quality to power AI/ML workflows in a hybrid, international environment.
Build and maintain scalable data pipelines and a high-performance Lakehouse for a biotech company, using Microsoft Fabric Data Factory to turn genomic and breeding data into FAIR assets for global R&D decisions.
Lead the design and implementation of a scalable data platform (Salesforce Data 360) and data lake, integrating ERP, CRM, and BI tools while ensuring governance and compliance.
Designs and automates scalable data pipelines for a biotech company, building a high-performance lakehouse to turn genomic and field data into FAIR assets for breeders and scientists.
Build and maintain scalable data pipelines using Microsoft Fabric to integrate and optimize data from ERP, CRM, and APIs for analytics and reporting.
Senior Data Engineer builds and scales a modern data platform using Databricks, PySpark, and Azure Data Factory to power advanced analytics, ML models, and near-real-time decision systems.
Build and maintain scalable data pipelines and a self-service data platform using Snowflake, Airflow, and AWS, enabling teams to produce and consume trusted data products.
Build and maintain data pipelines and ETL workflows in Python, orchestrating data ingestion from multiple sources for AI-driven fintech analytics and RAG systems.
Build and maintain data pipelines, manage distributed databases, and support development teams using SQL, PySpark, and streaming tech like Kafka.
Build and maintain scalable data pipelines and infrastructure using Databricks, Spark, ClickHouse, and Kafka to power real-time analytics and ML for mobile app monetization.
Build and own the data platform that powers AI model compression and quantum-inspired optimization products, designing ETL pipelines, lakehouse architectures, and governance workflows in Python/SQL on cloud platforms.
Build and own scalable data platforms and ETL pipelines for AI/ML and quantum-inspired optimization products, ensuring clean, versioned, and accessible datasets for analytics and AI workflows.
Build and evolve a global data platform using Microsoft Fabric, lakehouse architecture, and Azure, designing scalable pipelines and reusable data models for analytics and AI.
Build and maintain a cloud-based data lakehouse, design scalable data models, and develop ETL/ELT pipelines in AWS for analytics use cases across marketing, HR, and operations.
Design and maintain scalable data pipelines and warehouses for a global ad-tech platform, ensuring real-time data availability and quality for analytics and decision-making.
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