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This role seeks a Senior Data Architect instrumental in designing and implementing robust data quality solutions. You will champion strategies and processes ensuring data accuracy, completeness, and consistency across organizational systems, with a keen focus on Oracle ERP and SAP data. Utilizing Databricks, you will drive data processing and transformation, including the development and upkeep of ETL pipelines with PySpark.

Collaborate with business stakeholders and data engineers to grasp data quality needs for Oracle ERP, SAP, and Databricks environments. Design and deploy data quality solutions, encompassing cleansing, transformation, and validation for data from Oracle ERP and SAP, processed via Databricks using PySpark for ETL pipelines.

Establish comprehensive data quality standards, policies, and procedures tailored for Oracle ERP, SAP, and Databricks integration and processing. Select and implement appropriate data quality tools and technologies, including PySpark libraries within Databricks.

Monitor key data quality metrics across Oracle ERP, SAP, and Databricks, including ETL performance. Develop and implement data governance frameworks to ensure data quality and compliance. Take ownership of ETL framework and job performance, along with associated costs in production.

Partner with data analysts and scientists to guarantee the reliability and quality of data sourced from Oracle ERP and SAP, processed through Databricks, including data transformed by ETL pipelines. Document all data quality processes and solutions for future reference. Stay abreast of emerging trends and best practices in data quality technologies 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. A minimum of 12 years of experience as a Data Architect or in a comparable role is essential.

Possess extensive knowledge of data quality principles and methodologies as they apply to Oracle ERP, SAP systems, and big data processing in Databricks. Demonstrate experience in designing and implementing data quality solutions using tools compatible with Oracle ERP, SAP, and Databricks, such as data profiling, cleansing, and monitoring tools within Databricks.

Exhibit a strong grasp of Oracle ERP and SAP data models, functionalities, and integration points. Proven experience with Oracle and SAP data extraction, transformation, and loading (ETL) processes is necessary. Showcase expertise in using Databricks for data processing, transformation, and analytics, including developing and maintaining ETL pipelines with PySpark.

Be familiar with data quality best practices within enterprise resource planning (ERP) systems and big data processing. Strong analytical, problem-solving, and excellent communication and collaboration skills are paramount.