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Build and maintain cloud-native data pipelines on AWS, design scalable data lakes, and optimize relational/NoSQL databases to support energy-transition analytics and reporting.
Build Python applications with AI/LLM integrations and ML models, deploy on AWS/Azure, and implement ETL pipelines for fintech, logistics, and healthcare clients.
Builds scalable, secure cloud data pipelines on AWS using services like Glue, RDS, Redshift, and Kinesis.
Build and optimize data pipelines for commercial campaigns and predictive models in a retail bank using AWS S3, Glue, SQL, and Python.
Builds and maintains serverless ETL pipelines on AWS for a banking client, focusing on data governance and cataloging using Glue, Lambda, Step Functions, and PySpark.
Builds and maintains AWS-based data pipelines for a banking client, using Glue, Lambda, Step Functions, and PySpark to integrate, process, and catalog data.
Builds and maintains AWS-based ETL pipelines for a Peruvian bank using Glue, PySpark, and SQL, with optional Lambda/Step Functions orchestration.
Build and maintain cloud data pipelines for a banking client, migrating legacy systems to AWS (S3, Redshift, Athena) using Python, PySpark, and AWS Glue.
Senior Data Engineer builds and optimizes AWS-based data pipelines for a financial-sector client, using DBT, Airflow, Glue, Redshift and Python to transform and validate large datasets.
Build and maintain data pipelines on AWS for a banking client, using Python, Spark, Glue, and Step Functions to process and model large datasets.
Design and maintain AWS-based data pipelines, cloud data platforms, and AI/ML solutions using Python, Spark, and AWS services like S3, Glue, Redshift, and SageMaker.
Build and maintain scalable data infrastructure (AWS, Kafka, Spark, Airflow) to power analytics and AI-driven hiring products at a global job-tech platform.
Lead a team building a cloud-native operational data store (ODS) with Kafka, AWS Glue, and containerized services in a hybrid role based in Warsaw.
Build and maintain scalable data platforms on AWS using Kafka, Spark, Airflow and Iceberg to power analytics and AI products.
Build and maintain cloud-based data pipelines in Azure using Databricks, PySpark, and Python, collaborating on end-to-end data solutions for enterprise clients.
Build and maintain scalable AWS-based ETL/ELT pipelines using Glue, Spark, and SQL to feed data warehouses and analytics.
Design and build scalable AWS-based data pipelines using PySpark and AWS Glue, then monitor and optimize them for performance and reliability.
Designs and builds scalable AWS-based data pipelines using PySpark and AWS Glue to process and transform business data into reliable cloud architectures.
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.
Design and optimize Snowflake data warehouses for a pharma client, building ETL/ELT pipelines and dimensional models to support AI and analytics workloads.
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