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Designs and builds scalable data lake and warehouse solutions using SQL, Python, and cloud tools like Google Cloud Platform and Informatica Power Center.
Design and implement Azure Data Lake and Data Warehouse solutions using Python, SQL, Databricks, and event processing; mentor junior engineers in a hybrid work model.
Build and maintain scalable Azure-based ETL/ELT pipelines to integrate enterprise systems and transform raw data into analytics-ready insights for reporting.
Build and modernize Big Data pipelines for a European scoring agency using Azure Data Factory, Python/Java, and streaming tech like Kafka.
Design and build a scalable enterprise search engine for a global financial firm using Python, Spark, and Azure services.
Design and build Azure-based data pipelines, warehouses, and analytics using Databricks, Data Factory, and Power BI to process large datasets and enable ML workloads.
Designs and maintains scalable data pipelines and a central data platform using Databricks and Snowflake to power analytics and AI/ML across the organization.
Designs and maintains scalable data pipelines and a central data platform using Databricks, Snowflake, and Python to power analytics and AI/ML across the organization.
Design and implement Microsoft Fabric and Azure-based data pipelines, ETL/ELT processes, and AI-driven analytics solutions for enterprise clients.
Build and optimize Azure Data Factory/Synapse pipelines and Microsoft Fabric solutions, integrating AI-powered analytics and Power BI models to deliver business insights for clients.
Build and own the data platform for an AI-powered SaaS finance product, designing Snowflake pipelines, Power BI analytics, and AI-driven development workflows to deliver trusted insights for enterprise customers.
Build and maintain scalable ETL/ELT pipelines in AWS/Azure/GCP using Python, Spark, and SQL to power analytics and ML for global clients.
Senior Data Engineer builds and optimizes Azure-based ETL pipelines, data warehouses, and BI reports using SQL, Azure Synapse, and Power BI to deliver clean, governed data for analytics.
Senior Data Engineer builds and maintains cloud-based ETL pipelines and data architectures using Python, Spark, and cloud platforms to power analytics and ML for global clients.
Design and build large-scale data pipelines on Databricks using Python and cloud-native tools, ensuring secure, scalable data processing for downstream systems and reports.
Build and maintain data pipelines, warehouses, and lakes using Oracle, PostgreSQL, BigQuery, Kafka, and Python to feed analytics and reporting systems.
Build and maintain ETL pipelines using Spark/Scala to move and transform data between systems, ensuring quality and integration with microservices in a hybrid Warsaw role.
Design and build scalable AWS-based data pipelines and cloud-native architectures to process large datasets, using services like Glue, Redshift, Lambda, and Spark.
Build and maintain scalable ETL pipelines and data models using Spark, Scala, and cloud storage, then deliver clean data to analytics teams via BI tools like Databricks and Power BI.
Build and maintain scalable ETL/ELT pipelines and cloud-native data architectures using Python, Spark, and cloud platforms (AWS/Azure/GCP) to power analytics and ML for global clients.
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