Description

Lead end-to-end big data engineering projects, coordinating technical delivery across architecture, product, and QE teams. Drive multiple parallel projects from design through deployment.

Responsibilities

• Own the full development lifecycle including coding, testing, debugging, and deployment.
• Design and implement ETL pipelines for both batch and real-time data integration.
• Manage data ingestion, preparation, and operationalization to meet complex requirements.
• Coordinate technical requirements with architecture, BSA, and product leads.

Required Skills

• 5+ years of experience in data engineering and warehousing.
• Proficiency in PySpark and SQL.
• Hands-on experience with Azure Databricks and Azure Data Factory (ADF).
• Experience with Azure Synapse and cloud data warehouse architecture.
• Strong knowledge of ETL/ELT methodologies and data modeling.
• Expertise in relational technologies including MS SQL, SQL Server, and Delta Lake.
• Experience processing both structured and unstructured data.
• Practical use of Spark SQL and orchestration tools.
• Experience using Azure DevOps and GitHub for development workflows.
• Bachelor's Degree in a relevant field.

Preferred Skills

• Experience with SAS.

Key Skills

Education

Bachelor's Degree