Description

You will lead big data engineering efforts within capital markets projects, managing technical coordination across architecture, data engineering, and QE teams.

Responsibilities

• Drive multiple parallel projects from end-to-end development, including coding, testing, debugging, and deployment.
• Coordinate technical requirements with Product Group Leads, Architects, BSAs, and QE teams.
• Design and implement data integration, ingestion, and operationalization techniques for structured and unstructured data.
• Develop ETL pipelines for both batch and real-time data integration.
• Apply data modeling, architecture, and design principles to cloud data warehousing environments.

Required Skills

• 8+ years of experience in data engineering or related roles.
• Deep expertise in Capital Markets domain.
• Proficiency with Azure, PySpark, SQL, and Azure Data Factory (ADF).
• Hands-on experience with Azure Synapse and Databricks.
• Strong knowledge of ETL, Data Warehousing concepts, and methodologies.
• Experience with relational data processing using MS SQL, SQL Server, Spark SQL, and Delta Lake.
• Practical experience with orchestration tools, Azure DevOps, and GitHub.
• Ability to work with both structured and unstructured data.

Preferred Skills

• Experience with SAS.

Key Skills

Education

Not specified