Elevate your career at EY and become the best version of yourself within a global, inclusive culture. We seek a highly skilled Senior Data Architect, a pivotal role in shaping our data landscape. This position focuses on leveraging extensive expertise in Oracle ERP, SAP, and Databricks to design and implement robust data quality solutions. You will be instrumental in developing strategies and processes that guarantee the accuracy, completeness, and consistency of our organizational data, with a special emphasis on Oracle ERP and SAP systems. Utilizing Databricks, you will drive data processing and transformation, including the creation and maintenance of sophisticated ETL pipelines with PySpark.

Collaborate closely with business stakeholders and data engineers to deeply understand data quality needs and challenges within Oracle ERP, SAP, and big data environments using Databricks, including ETL development. Design and implement comprehensive data quality solutions, encompassing data cleansing, transformation, and validation for data from Oracle ERP, SAP, and processed via Databricks, using PySpark for ETL pipeline development. Establish and maintain data quality standards, policies, and procedures specifically for Oracle ERP, SAP, and Databricks data integration, processing, and ETL. Select and deploy data quality tools and technologies that integrate seamlessly with Oracle ERP, SAP, and Databricks, including PySpark functionalities for ETL. Continuously monitor and assess data quality metrics across Oracle ERP, SAP, and Databricks pipelines, paying close attention to ETL performance and data integrity within these processes. Develop and implement effective data governance frameworks to uphold data quality and ensure compliance, with a focus on Oracle ERP, SAP, and Databricks data integration and ETL. Take ownership of ETL framework and job performance and cost management in production environments. Partner with data analysts and scientists to ensure the reliability and quality of data from Oracle ERP, SAP, and processed through Databricks, including data transformed via ETL pipelines. Create thorough documentation for data quality processes and solutions, specifically detailing Oracle ERP, SAP, and Databricks data integration and ETL. Stay abreast of emerging trends and innovations in data quality technologies and best practices, particularly those relevant to Oracle ERP, SAP, Databricks, and PySpark for ETL.

A Bachelor’s degree in Computer Science, Information Technology, or a related discipline is required, with a Master’s degree being preferred. Possess a minimum of 12 years of experience in a Data Architect or a comparable role. Demonstrate extensive knowledge of data quality principles and methodologies as they apply to Oracle ERP, SAP systems, and big data processing within Databricks. Proven experience in designing and implementing data quality solutions using various tools and technologies compatible with Oracle ERP, SAP, and Databricks. Exhibit a strong comprehension of Oracle ERP and SAP data models, functionalities, and integration capabilities. Possess practical experience with Oracle and SAP data extraction, transformation, and loading (ETL) processes. Showcase expertise in utilizing Databricks for data processing, transformation, and analytics workflows, including building and maintaining ETL pipelines with PySpark. Be familiar with data quality best practices in the context of enterprise resource planning (ERP) systems and big data processing. Exhibit strong analytical and problem-solving abilities. Possess excellent communication and collaboration skills.