About

Data engineering is the backbone of modern data-driven organizations. By designing and building robust data infrastructure for data-driven decisions. My expertise lies in extracting, transforming, and loading data for optimal business outcomes

Data Engineering Cookbooks

Technologies: PostgreSQL/Python/Apache NiFi/Apache Airflow/Elastic Search/Kibana/Docker


Data Engineering Github Wiki


pgsql Right pgsql nifi airflow docker

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Azure and SQL Server Integration Services (SSIS)

Technologies: Azure/SQL/SSIS/Python/Regex


Azure and SSIS Github Wiki

Microsoft_Azure_Logo

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AWS for Data Science Pipelines and Machine Learning

Technologies: AWS/SQL/Python


AWS (Amazon Web Services) Github Wiki

AWS Solution Categories

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Apache Spark

Technologies: MLlib/Streaming/SQl/GraphX


Apache Spark Github Wiki


etl Batch/streaming data sql-analytics-icon data-science-scale-icon Batch/machine-learning-icon

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Data Bricks

Technologies: MLlib/Streaming/SQl/GraphX


Data Bricks Github Wiki


databricks etl

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Web Scrapping Infrastructure

Technologies: MLlib/Streaming/SQl/GraphX


Webscrapper Github


etl

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© SimonRenauld