Senior Data Engineer – Azure Databricks & Workday GL Integration

About the role

Our client, a leading multinational telecommunications organization, is launching a Workday General Ledger integration programme. They are seeking two Senior Data Engineers to design, build and maintain an automated, governed financial data pipeline on Azure Databricks that feeds validated journal entries into Workday Financial Management.

Key responsibilities

• Design, develop and operate production‑grade ETL pipelines using Azure Databricks, PySpark and Python.
• Build and manage Delta Lake tables, Unity Catalog and Lakehouse layers (Bronze, Silver, Gold).
• Implement reusable notebooks, Databricks Workflows and automated data‑quality checks.
• Develop REST/SOAP API integrations with authentication, retries, error handling and audit logging.
• Translate finance business rules into configurable pipeline logic, including KPI‑to‑GL mapping and chart‑of‑accounts handling.
• Create automated reconciliation processes and SOX‑compliant maker/checker/approver controls.
• Support system integration testing, UAT, parallel runs and post‑go‑live monitoring.
• Produce technical documentation, runbooks and operational dashboards.

Required profile

• Bachelor’s degree in Computer Science, Data Engineering, IT, Mathematics or a related field.
• Minimum 3 years of professional experience in Data Engineering or Analytics Engineering.
• Strong hands‑on experience with Azure Databricks, Python, PySpark and SQL.
• Experience with Delta Lake, Unity Catalog and Azure data services.
• Ability to work closely with finance stakeholders and external technology partners.

Required skills

• Azure Databricks
• Python
• PySpark
• SQL
• Delta Lake
• Unity Catalog
• Azure data services (e.g., Azure Data Factory, Blob Storage)
• REST and SOAP API integration
• Workday Financial Management / GL integration concepts