Senior Data Engineer

Job Title: Hybrid Data Engineer Databricks Focus

Location:

Job Type:

About the Role:

Data Engineer

Key Responsibilities:

• Develop, maintain, and optimize data pipelines in

  Databricks

  .
• Validate and reconcile SAP-derived spend data from the Data Lake.
• Support the creation of a supplier hierarchy using external APIs (e.g., Moody’s).
• Manage delta refresh processes for monthly SAP data loads, ensuring data quality.
• Enhance or fix EDF algorithms (e.g., deduplication, transaction tracking).
• Integrate external datasets (Moody’s, S&P, etc.) into the spend data ecosystem.
• Prepare and curate datasets for visualization and reporting (Power BI).
• Contribute to building a connected data foundation for future GenAI-based solutions (e.g., Teams chatbot).

Nice to Have:

• Experience with

  Power BI

  for reporting and dashboarding.
• Familiarity with item-level taxonomy and hierarchical data modeling.
• Knowledge of SAP data structures and procurement/spend data.
• Experience working with third-party data enrichment APIs.
• Exposure to AI/ML or chatbot integration is a bonus.

Requirements:

• 3–6 years of experience in

  Data Engineering

  roles.
• Strong proficiency in

  Databricks

  ,

  PySpark

  , and large-scale data processing.
• Understanding of data quality and data governance best practices.
• Excellent problem-solving skills and ability to work cross-functionally.