Enterprise Solutions Architect

As a Senior Data Architect, you will play a crucial role in designing and implementing scalable, secure, and high-performance Big Data architectures using Databricks, Apache Spark, and cloud-native services. Your expertise will be essential in leading the end-to-end data architecture lifecycle, from requirements gathering to deployment and optimization. Additionally, you will design repeatable and reusable data ingestion pipelines for various ERP source systems like SAP, Salesforce, HR, Factory, and Marketing systems. Collaboration with cross-functional teams to integrate SAP data sources into modern data platforms will be a key aspect of your role, along with driving cloud cost optimization strategies and ensuring efficient resource utilization. Furthermore, you will provide technical leadership and mentorship to a team of data engineers and developers, while also developing and enforcing data governance, data quality, and security standards. Your ability to translate complex business requirements into technical solutions and data models will be crucial, as well as staying current with emerging technologies and industry trends in data architecture and analytics. Your skill set should include proven expertise in Databricks, Apache Spark, Delta Lake, and MLflow, along with strong programming skills in Python, SQL, and PySpark. Experience with SAP data extraction and integration, as well as hands-on experience with cloud platforms like Azure, AWS, or GCP, will be highly beneficial. Required qualifications include a minimum of 6 years of experience in Big Data architecture, Data Engineering, and AI-assisted BI solutions within Databricks and AWS technologies. A bachelor's degree in computer science, information technology, data science, data analytics, or related field is necessary. Additionally, you should have a solid understanding of data modeling, ETL/ELT pipelines, and data warehousing, along with demonstrated team leadership and project management capabilities. Strong communication, problem-solving, and stakeholder management skills are essential for success in this role. Preferred qualifications include experience in the manufacturing domain, certifications in Databricks, cloud platforms, or data architecture, and familiarity with CI/CD pipelines, DevOps practices, and infrastructure as code (e.g., Terraform).,