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Senior Data Engineer designs and builds cloud-based data pipelines, warehouses, and ETL/ELT workflows using GCP, Azure, Snowflake, and dbt to support BI and AI systems.
Designs and builds scalable data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory to integrate diverse data sources.
Designs and builds Azure Databricks-based data pipelines and Lakehouse architectures using Spark and Delta Lake, integrating with SQL Server for analytics and BI.
Build and optimize Azure Databricks-based data pipelines and Lakehouse architectures using PySpark and Azure Data Factory to power scalable cloud analytics and BI reporting.
Build and maintain Azure and Databricks cloud data pipelines, transform data with SQL and PySpark, and collaborate on scalable data solutions in a hands-on GenAI/LLM environment.
Builds and maintains scalable data pipelines and lakehouse infrastructure for AI/ML workloads using Python, Java, SQL, and Spark.
Senior Data Engineer builds and optimizes Databricks Lakehouse pipelines in Azure, using PySpark to create scalable data models and incremental loads for large datasets.
Senior Data Engineer builds scalable Lakehouse architectures and ETL/ELT pipelines using Databricks, Spark, and cloud services to turn logistics data into BI insights and support analytics across Azure, AWS, or GCP.
Builds and optimizes ETL pipelines for a lakehouse architecture using Python/Spark, SQL, and cloud tools to support enterprise-scale data workloads in Commercial Risk Solutions.
Designs and builds scalable data pipelines and lakehouse architecture for enterprise analytics, while mentoring engineers and enforcing data governance and security.
Senior AI & Data Engineer builds AI-powered solutions using Python, LLMs, and RAG pipelines, integrating them into production systems with Azure services.
Designs and builds a Lakehouse data platform and BI pipelines using Databricks, Spark, and Power BI to power global analytics at a logistics company.
Build and operate Snowflake-based data platforms that power GenAI and advanced AI use cases at enterprise scale, integrating vector search, RAG, and agent workflows.
Builds and maintains data platforms using Azure, Databricks, and AWS, focusing on Lakehouse architectures, ETL/ELT pipelines, and high-quality data delivery for analytics and AI teams.
Designs and maintains data pipelines for a lakehouse and AI platform at a global investment bank, using Python/Java and distributed processing frameworks.
Builds and maintains AWS-based lakehouse and real-time data pipelines using Debezium, Kafka, PySpark and SQL to deliver trusted datasets for business users.
Senior Data Engineer builds and optimizes a lakehouse architecture and ClickHouse deployments, plus ETL/ELT pipelines for a Polish real-estate firm using Python and SQL.
Build and maintain scalable data pipelines and Lakehouse architectures using Databricks, PySpark, and Delta Lake to power analytics and GenAI solutions for enterprise clients.
Senior Data Engineer builds and maintains scalable data pipelines and lakehouse platforms using Databricks (Spark, Delta Lake), Python, and SQL to support anti-financial-crime analytics for PwC’s global clients.
Design and build scalable Lakehouse architectures (Bronze/Silver/Gold) using Databricks and Delta Lake to transform logistics data into BI insights, optimizing ETL/ELT pipelines with PySpark and Azure/AWS/GCP services.
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