Description

Design, build, and maintain fault-tolerant data pipelines to support reporting, analysis, and data science requirements. You will own the full lifecycle of data systems, from architecture to operational optimization.

Responsibilities

• Design and refactor data pipelines to improve quality, performance, and reliability.
• Implement DataOps and MLOps standards to streamline data system performance.
• Lead root cause analysis to optimize data delivery and reduce operational costs.
• Mentor data engineers at all experience levels and lead delivery teams.
• Engage business end users to translate requirements into technical solutions.

Required Skills

• 7+ years of proven Data Engineering experience in complex agile environments.
• Advanced experience with Microsoft Azure, Azure Data Factory, and Azure Synapse.
• Proficiency in Python and PySpark for data manipulation and processing.
• Extensive experience with Databricks and SQL.
• Strong knowledge of Azure DevOps, GitHub, and CI/CD workflows.
• Experience with database storage systems including relational, data lake, and data warehouse.
• Proven ability to build cloud ETL pipelines using APIs, database connections, or file-based methods.
• Deep understanding of data warehousing concepts and agile methodology.
• Bachelor's degree in Computer Science, Software Engineering, IT, or equivalent experience.

Preferred Skills

• Experience with Power BI or other cloud-based data systems.

Key Skills

Education

Bachelor's degree