Responsibilities:

1. Data Pipeline Development:

· Design, build, and maintain efficient ETL pipelines to process and transform data.

· Ensure pipelines integrate seamlessly with the o9 platform and other systems.

2. Data Quality and Validation:

· Perform rigorous data validation to ensure accuracy and consistency.

· Implement monitoring tools and practices to detect and address data anomalies.

3. Data Modeling and Optimization:

· Develop and optimize data models to support MFP, AP and demand planning analytics.

· Create scalable solutions for handling large data sets to support regional growth.

4. Collaboration and Support:

· Work with BSAs, system engineers, and product managers to understand data needs and provide technical solutions.

· Provide support for data-related issues, troubleshooting root causes, and implementing fixes.

5. Documentation and Knowledge Sharing:

· Document data pipeline processes, data models, and resolution steps.

· Share knowledge and best practices with the team for maintaining data quality.

6. Process Improvement:

· Continuously evaluate and enhance data pipelines for better performance and reliability.

· Stay updated on emerging tools and technologies to improve data engineering processes.

Qualifications:

· Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.

· Proficiency in ETL process, SQL, data modeling, and cloud platforms (e.g., AWS, GCP, Azure).

· 3+ years in data engineering, preferably in supply chain or planning domains; familiarity with enterprise planning tools like o9 or SAP is a plus.

· Strong problem-solving skills with expertise in analyzing and optimizing data pipelines.

· Excellent communication skills for cross-functional teamwork with technical and non-technical stakeholders.

· Experience with big data technologies (e.g., Hadoop, Spark), reporting tools (e.g., Power BI, Tableau), and ITSM practices (e.g., Jira, Confluence) preferred.