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Data architect with AI ML at Remote, Remote, USA
Email: [email protected]
From:

Naresh,

Avance Consulting

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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
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Sat Jun 01 08:17:00 UTC 2024

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