SENIOR AZURE DATA ENGINEER

Project description We are seeking a highly skilled and experienced Senior Azure Data Engineer to join our dynamic team.
The ideal candidate will possess strong technical expertise in Azure, PySpark, Python, ADF (Azure Data Factory), SQL, and GitHub.
This role requires a proactive individual who can design, develop, and maintain data solutions on the Azure platform, ensuring high performance and reliability.
Responsibilities Design, build, and maintain scalable data pipelines on Azure Databricks and Google Cloud Platform (GCP) using PySpark and Python.
Work with Azure and GCP platforms, specifically managing services like Azure Databricks, Azure SQL Server, BigQuery, DataProc, and Azure Machine Learning.
Develop and maintain CI/CD pipelines using GitHub Actions to automate the deployment of data engineering solutions.
Utilize GitHub for version control, ensuring that all code changes are tracked, reviewed, and managed effectively.
Work closely with cross-functional teams to define requirements, design solutions, and deliver high-quality data engineering outputs.
SKILLS Must have It is expected that the engineer.
nIs proficient in Data Engineering concepts (Object Storage, Data Pipelines, ELTs, Data Modeling, etc.)nIs proficient in Software Engineering concepts (Continuous Integration, Continuous Deployment, Unit Testing, Coverage, Linting, Version Control System, etc.)nHave knowledge or understanding the basic concepts of Software Development lifecycle (Release Engineering, Deployments, Code review, Requirements definition)nnPlatforms - Azure Databricks, SQL Server, Azure Machine Learning, Azure Blob StoragennProgramming Language - Python, PySparknnCI/CD - GitHub Actions, GitHubnnVCS - GitHub Nice to have It is expected that the Engineer.
Has the general P&G Training to be following any P&G IT Policy.
Is vetted to work with POS (Point of Sale) data.
Has all the accesses to work with P&G Clouds (GCP and Azure), which should have VMs with access points to PGI Endpoints.
Preferably to have a MacOS or a Linux computer.
Design, build, and maintain scalable data pipelines on Azure Databricks and Google Cloud Platform (GCP) using PySpark and Python.
Work with Azure and GCP platforms, specifically managing services like Azure Databricks, Azure SQL Server, BigQuery, DataProc, and Azure Machine Learning.
Develop and maintain CI/CD pipelines using GitHub Actions to automate the deployment of data engineering solutions.
Utilize GitHub for version control, ensuring that all code changes are tracked, reviewed, and managed effectively.
Work closely with cross-functional teams to define requirements, design solutions, and deliver high-quality data engineering outputs.
It is expected that the engineer.
nIs proficient in Data Engineering concepts (Object Storage, Data Pipelines, ELTs, Data Modeling, etc.)nIs proficient in Software Engineering concepts (Continuous Integration, Continuous Deployment, Unit Testing, Coverage, Linting, Version Control System, etc.)nHave knowledge or understanding the basic concepts of Software Development lifecycle (Release Engineering, Deployments, Code review, Requirements definition)nnPlatforms - Azure Databricks, SQL Server, Azure Machine Learning, Azure Blob StoragennProgramming Language - Python, PySparknnCI/CD - GitHub Actions, GitHubnnVCS - GitHub