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Build and maintain scalable data pipelines and lakehouse architectures on Azure/Databricks, enabling analytics and reporting for HR and people operations.
Design and implement end-to-end AI solutions using Python, PySpark, Databricks, Postgres and open-source LLMs like Qwen, building data pipelines, RAG systems and AI agents for enterprise clients.
Build and maintain Azure-based data and ML pipelines for Burger King, Popeyes, and Tim Hortons, focusing on Databricks, Azure ML, AKS, and MLOps workflows.
Build and maintain a Lakehouse data platform using PySpark and Databricks, designing Delta Lake schemas and batch/near-real-time pipelines for analytics and data sharing.
Build and optimize Databricks-based data platforms and pipelines for Fortune 1000 clients, leveraging Spark, Delta Lake, and multi-cloud (AWS/Azure/GCP) to deliver scalable analytics and insights.
Builds batch and near-real-time data pipelines in PySpark on Databricks, designs Delta Lake schemas, and collaborates with product/QA to deliver reliable data products.
Build and scale data-driven and generative AI solutions for global clients in banking, pharma, and public sector using cloud platforms, Spark, and Azure OpenAI.
Builds and maintains a PySpark and Delta Lake data lakehouse on Databricks, creating batch and near-real-time pipelines to power analytics and data sharing for a product suite.
Build and maintain secure, scalable cloud data platforms using Databricks, AWS services, and Terraform to enable governed data processing and analytics.
Build and optimize cloud-based data pipelines using Spark on Databricks, MongoDB, Delta Lake, Airflow and Azure Data Factory to turn raw data into scalable, production-grade analytics platforms.
Build and maintain scalable data pipelines and platforms for Proton’s privacy-focused products using Scala/Java/Python and Spark, ensuring reliable analytics and insights.
Build and maintain GCP cloud infrastructure for Booksy’s data ecosystem, automating pipelines with Terraform and CI/CD to support analytics teams.
Maintain and optimize a corporate data lake using AWS, Spark, Kafka, and Python, ensuring scalable data processing and performance.
Build and optimize large-scale data pipelines using Scala/Spark and AWS to power analytics, ML, and reporting for a digital bank, ensuring reliable data flows for business decisions.
Builds and maintains scalable data pipelines on Azure using Spark, Databricks, Delta Lake, and Airflow to support digital-transformation projects in a multicultural team.
Designs and maintains scalable data pipelines on Databricks using Spark, Delta Lake, and Unity Catalog, collaborating with data scientists and architects.
Senior Data Engineer builds and maintains Databricks data pipelines on Azure/AWS, migrates legacy systems, and designs Delta Lake architectures for multi-tenant clients.
Senior Data Engineer builds and governs scalable data pipelines on Databricks/Azure, enabling AI and analytics across Axpo’s climate-tech platform.
Build and optimize scalable data pipelines on Databricks using Spark, Delta Lake, and Unity Catalog to power analytics and ML workflows for enterprise clients.
Leads data engineering projects, mentors junior engineers, and delivers training on Databricks, Snowflake, and dbt while supporting pre-sales with technical solutions.
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