As part of a key initiative to expand our Supply Chain Analytics team, we are seeking a Data Engineer to lead and support data ingestion, preparation, processing, and delivery using MS Azure services.
responsibilities :
Design, optimize, and maintain large-scale data pipelines (ETL/ELT) to enable business intelligence and statistical modeling.
Ensure data quality and integrity through continuous monitoring and validation.
Set up and manage data storage solutions (e.g., SQL databases, data lakes).
Oversee and support production workflows that connect critical components of the data infrastructure.
Write and maintain secure, scalable, efficient, and reliable code to transform business requirements into functional solutions.
Promote best engineering practices, including automation, CI/CD processes, and code maintainability.
Drive standardization and automation efforts by adhering to common development guidelines and industry best practices.
Collaborate with BI analysts, data scientists, machine learning engineers, and core IT teams in cross-functional projects to deliver data-driven solutions.
requirements-expected :
Strong proficiency in Python, SQL, MDX, and Bash scripting.
2+ years of hands-on experience with Azure data tools (e.g., Data Factory, Synapse, Data Lake, Blob Storage, SharePoint, Databricks).
Practical experience with data workflow orchestration tools (ADF, Databricks Jobs, or Airflow).
Solid understanding of version control systems and CI/CD pipelines using Azure DevOps or similar tools.
Experience working with Snowflake in an Azure cloud environment.
Familiarity with data governance concepts (e.g., data cataloging, metadata management, data lineage, master data, security, and compliance).
