Data Engineer for HR Analytics and Reporting

About the job

As a Data Engineer for HR Analytics and Reporting, your role involves designing and developing scalable data pipelines. You will be responsible for integrating data from Oracle HR systems and third-party sources. Your expertise will be crucial in optimizing SQL queries and ETL processes for performance and accuracy. Collaboration with HR analysts and data scientists is essential to ensure the delivery of reliable datasets. Additionally, you will play a key role in maintaining data quality, consistency, and security across platforms. Documentation of workflows, data models, and technical processes is also part of your responsibilities. Key Responsibilities: - Design and develop scalable data pipelines for HR analytics and reporting. - Integrate data from Oracle HR systems and third-party sources. - Optimize SQL queries and ETL processes for performance and accuracy. - Collaborate with HR analysts and data scientists to deliver reliable datasets. - Ensure data quality, consistency, and security across platforms. - Document workflows, data models, and technical processes. Qualifications Required: - 1+ years of experience in data engineering, data analytics, or related field. - Strong SQL skills and familiarity with ETL tools like ODI. - Experience with Python, R, or similar scripting languages. - Knowledge of data warehousing concepts and relational databases (e.g., Oracle, MySQL). - Understanding of HR data (e.g., employee lifecycle, organization hierarchy) is a plus. - Bachelor's degree in Computer Science, Information Systems, Data Science, or related field. In addition to the qualifications required, the following skills are preferred: - Experience working with Oracle Cloud Infrastructure (OCI). - Familiarity with Oracle HCM Cloud or other HRIS platforms. - Interest in using AI and machine learning to improve HR processes.

Requirements

• Data Engineering
• SQL
• ETL
• Python
• Data Analysis

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Science, or related field

Preferred Technologies

• Data Engineering
• SQL
• ETL
• Python
• Data Analysis