| Data architect with AI ML at Remote, Remote, USA |
| Email: [email protected] |
| From: Naresh, Avance Consulting [email protected] Reply to: [email protected] Role:Data architect with AI /ML Location: Middletown,New Jersey,United States You can reach me at mailto [email protected] Hybrid Skills : SQL, Python, and R., Azure, Databricks, and Synapse,data warehousing, ETL processes AI/ML model Job Description Qualifications Experience: Minimum of 15+ years of experience in data architecture, with at least 5 years of hands-on experience with Azure, Databricks, and Synapse. Technical Skills: Proficient in SQL, Python, and/or R. Strong knowledge of data warehousing, ETL processes, and AI/ML model development. Certifications: Relevant certifications such as Azure Solutions Architect, Databricks Certified Data Engineer, or equivalent are highly desirable. Soft Skills: Excellent problem-solving skills, strong communication abilities, and a collaborative mindset. Key Responsibilities Architecture Design and Strategy Develop comprehensive data architecture strategies and solutions using Azure, Databricks, and Synapse. Design scalable and secure data pipelines, storage solutions, and AI models to support business objectives. Implementation and Development Lead the implementation of data solutions, ensuring best practices in data management, transformation, and analysis. Utilize Databricks for advanced analytics and AI model development, ensuring seamless integration with Synapse for data warehousing. Collaboration and Leadership Collaborate with cross-functional teams including data scientists, data engineers, and business analysts to understand requirements and deliver solutions. Provide technical leadership and mentorship to team members, fostering a culture of innovation and continuous improvement. Data Governance and Compliance Ensure all data solutions comply with industry standards and regulatory requirements. Implement robust data governance frameworks to maintain data quality, integrity, and security. Performance Optimization Monitor and optimize the performance of data pipelines and AI models, ensuring efficient resource utilization. Troubleshoot and resolve any issues related to data integration and processing. Innovation and Continuous Improvement Stay updated with the latest trends and advancements in data architecture, AI, and cloud technologies. Propose and implement innovative solutions to enhance data processing capabilities and AI model accuracy. Technical Documentation Develop and maintain detailed technical documentation for all data architectures, processes, and AI models. Ensure documentation is up-to-date and accessible to relevant stakeholders. Stakeholder Management Engage with key stakeholders to understand business needs and translate them into technical requirements. Communicate complex technical concepts to non-technical stakeholders effectively. Project Management Manage multiple projects simultaneously, ensuring timely delivery and alignment with business goals. Use project management tools and methodologies to track progress and manage risks. Vendor and Tool Evaluation Evaluate and recommend tools, technologies, and vendors to enhance the data architecture and AI capabilities. Conduct proof-of-concepts and pilot projects to assess new solutions and their fit for the organization. Keywords: artificial intelligence machine learning rlang Data architect with AI ML [email protected] |
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| Sat Jun 01 08:17:00 UTC 2024 |