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Middletown

    Senior Data Architect - Middletown, United States - Avance Consulting

    Avance Consulting
    Avance Consulting Middletown, United States

    6 days ago

    Default job background
    Description

    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

    1. 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.
    1. 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.
    1. 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.
    1. 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.
    1. 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.
    1. 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.
    1. 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.
    1. 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.
    1. 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.
    1. 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.
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