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Design and build scalable data pipelines and architectures using AWS and Databricks, focusing on PySpark, Python, and SQL to enable advanced analytics and ETL workflows for enterprise clients.
Designs and builds scalable AWS data pipelines using PySpark, Python, AWS Glue, and serverless components, with IaC via Terraform and CI/CD practices.
Designs and maintains ETL pipelines to ingest, clean, and warehouse large-scale data for Sea’s finance team, enabling accurate reporting and analysis across Garena, Shopee, and Monee.
Design and maintain scalable data pipelines and ETL processes using SQL, Python, Databricks, and PySpark to deliver reliable, high-quality data solutions for analytics and reporting.
Senior data engineer builds and maintains Databricks-based data warehouse and real-time pipelines for a financial trading business, modeling trades, positions, and market data.
Lead a small team to design, build, and scale cloud-based data pipelines and platforms using Python, SQL, and tools like Airflow, Spark, and Snowflake for reliable, ML-ready data.
Designs and maintains scalable cloud data pipelines and warehouses using SQL, Python, and cloud platforms to enable reliable analytics and business insights.
Build and maintain Azure-based data pipelines with PySpark and Databricks to integrate on-prem and cloud data for HR payroll analytics in a hybrid Kraków team.
Senior Data Engineer builds and optimizes scalable data pipelines and ETL processes for HEINEKEN’s global data infrastructure, using Python, SQL, Azure, Databricks, and Kafka.
Build and maintain ETL/ELT pipelines and modern data platforms using Azure services, Databricks, and PySpark.
Build and maintain scalable data pipelines on Azure and Databricks, using PySpark, SQL, and ETL/ELT processes to support analytics and reporting.
Builds and maintains Azure-based data pipelines using PySpark and Databricks to integrate and deliver data for business analytics across payroll projects.
Build and maintain scalable data pipelines using PySpark, AWS, and Terraform to support analytics and infrastructure automation in an international team.
Build and maintain cloud data pipelines using Azure Databricks, PySpark, and Delta Lake to feed analytics and BI tools, integrating with SQL Server and Azure Data Factory.
Build and maintain big-data pipelines and cloud infrastructure using PySpark, AWS, and Terraform to process and optimize data solutions for an international team.
Design and maintain scalable data pipelines and enterprise data warehouses using AWS Glue, PySpark, and Informatica to ingest, transform, and deliver clean data for analytics across Schneider Electric’s global operations.
Build and deploy ML models and data pipelines to optimize ad-tech performance, collaborating with engineers and product teams using Python, SQL, and frameworks like TensorFlow.
Line of Service Advisory Industry/Sector Not Applicable Specialism Technology Strategy Management Level Senior Manager Job Description & Summary At PwC, our people in data and analytics focus on leveraging data to…
Build and maintain Databricks/PySpark pipelines on Azure to ingest and transform supply-chain data for a visibility platform.
Builds and scales a full-stack analytics platform with PySpark, Hadoop, and Databricks SQL, exposing prediction and credit-risk APIs for fintech use cases.
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