We are seeking a Senior Data Warehouse Engineer with a background in Oracle E-Business Suite (EBS) and Python-based data engineering to design, develop, and maintain enterprise data solutions. The ideal candidate will have hands-on experience building and optimizing data pipelines, integrating ERP data into warehouse environments, and enabling analytics and reporting across business domains such as Finance, Supply Chain, HR, and Manufacturing.
Key Responsibilities
- Design, develop, and maintain data warehouse architectures supporting enterprise analytics and reporting.
- Extract, transform, and load (ETL/ELT) data from Oracle E-Business Suite (EBS) and other enterprise systems into the warehouse (e.g., Snowflake, BigQuery, Redshift, or Oracle DW).
- Develop efficient and reusable Python scripts for data ingestion, transformation, and validation.
- Build and optimize SQL and PL/SQL queries, stored procedures, and views for high-performance data access.
- Work with business analysts, functional teams, and ERP specialists to understand data models and reporting needs.
- Ensure data quality, lineage, and consistency across multiple systems.
- Participate in data modeling (conceptual, logical, and physical) for warehouse and reporting layers.
- Automate workflows and data pipelines using Airflow, DBT, or similar orchestration tools.
- Troubleshoot and optimize data pipelines for performance and scalability.
- Implement best practices for data governance, metadata management, and security.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
- 8+ years of experience in data warehousing and ETL development, including hands-on experience with Oracle E-Business Suite data structures and APIs.
- Strong SQL and PL/SQL skills, with experience in query optimization and complex joins.
- Proficiency in Python for data processing, automation, and integration tasks.
- Experience with ETL tools such as Informatica, ODI, Talend, or custom Python-based ETL frameworks.
- Solid understanding of data modeling principles (Kimball or Inmon methodologies).
- Experience with data orchestration tools (e.g., Apache Airflow, Control-M, or Azure Data Factory).
- Familiarity with cloud-based data platforms (Snowflake, Redshift, BigQuery, or Oracle Cloud).
- Knowledge of EBS modules (Finance, SCM, HR, Manufacturing) and underlying data structures.\
Preferred Qualifications
- Experience integrating EBS data with modern BI tools (Power BI, Tableau, or Oracle Analytics).
- Working knowledge of API integrations (REST/SOAP) to extract EBS or external system data.
- Exposure to DataOps practices, Git-based version control, and CI/CD for data pipelines.
- Understanding of data governance frameworks (e.g., Collibra, Alation, or Data Catalogs).
- Strong problem-solving, analytical thinking, and communication skills.