Data/Machine Learning Solutions Architect with AWS

USA
General and Administration – GM - Matt Ewalt /
Full-time /
Remote
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Provectus, is a leading AI consultancy and solutions provider specializing in Data Engineering and Machine Learning. With a focus on helping businesses unlock the power of their data, we leverage the latest technologies to build innovative data platforms that drive results. Our Data Engineering team consists of top-tier professionals who design, implement, and optimize scalable, data-driven architectures for clients across various industries.

Join us if you have the same passion for making products using AI/ML technologies, cloud services, and data engineering.

As a Data Solutions Architect, you will lead the design, architecture, and implementation of large-scale data solutions for our clients. You will act as a strategic technical leader, collaborating with cross-functional teams to deliver innovative data platforms that drive business value.

Responsibilities:

    • Strategic Technical Leadership:
      • - Lead high-impact customer engagements focused on AWS Data Platform/ ML solutions.
      - Define and drive technical strategies that align AWS capabilities with customer objectives, incorporating Databricks, GCP, or Azure where appropriate.
    • Solution Architecture and Design:
      • - Lead the design and implementation of data and AI/ML architecture solutions across cloud and on-premise platforms, ensuring optimal performance, security, and cost-efficiency..     
      - Design and execute proofs of concept for emerging technologies like Generative AI, Machine Learning
      - Integrate AWS services with other solutions (Databricks, Snowflake, GCP, or Azure) as needed, selecting the right technologies and tools to meet customer needs.
      - Develop and maintain comprehensive architectural documentation aligned with organizational technical standards.
    • Pre-Sales Activities:
      • - Partner with the sales team, providing technical expertise to position AWS-based data solutions effectively.
      - Participate in customer meetings to assess technical needs, scope solutions, and identify growth opportunities.
      - Create technical proposals, solution architectures, and presentations to support sales efforts and align with customer expectations.
      - Assist in responding to RFPs/RFIs with accurate technical input and align solutions to client requirements.
      - Demonstrate AWS capabilities through POCs and technical demonstrations to showcase proposed solutions.
    • Customer Engagement and Relationship Management:
      • - Build and maintain strong relationships with key customer stakeholders, acting as a trusted advisor for data platform initiatives.
      - Lead discovery workshops to understand customer requirements, KPIs, and technical constraints.
    • Project Leadership and Delivery:
      • - Oversee the end-to-end implementation of AWS-based data platforms, coordinating with engineering teams to ensure successful delivery.
      - Manage technical risks and develop mitigation strategies.
    • Innovation and Best Practices:
      • - Stay up-to-date with the latest developments in AWS, Databricks, GCP, Azure, and cloud technologies.
      - Develop and promote best practices in data platform architecture, data pipelines, and data governance.
    • Cross-Functional Collaboration:
      • - Collaborate with AI/ML teams to integrate advanced analytics and machine learning capabilities into AWS and other cloud platforms.
      - Work with DevOps teams to implement CI/CD pipelines and automation for data workflows.
    • Mentorship and Knowledge Sharing:
      • - Mentor junior architects and engineers, fostering a culture of continuous learning and professional development.
      - Contribute to knowledge-sharing initiatives through technical blogs, case studies, and industry event presentations.
    • Governance, Compliance, and Security:
      • - Ensure that AWS-based data platform solutions comply with relevant security standards and regulations.
      - Implement data governance frameworks to maintain data quality and integrity.

Requirements:

    • Experience in data solution architecture.
    • Strong understanding of AI/ML concepts and experience integrating AI/ML components into solutions.
    • Technical sales or pre-sales experience with cloud, Big Data, and ML solutions.
    • Proven experience in designing and implementing large-scale data engineering solutions on AWS.
    • Experience with Databricks, GCP, or Azure solutions is required.
    • Deep expertise in AWS platform services, including S3, EC2, Lambda, EMR, Glue, Redshift, AWS MSK, and EKS.
    • Proficiency in any of the backend-related languages: TS, Java, Python, Scala, and others.
    • Experience with data warehousing, ETL processes, and real-time data streaming.
    • Familiarity with open-source technologies and tools in data engineering.
    • Solid understanding of machine learning and MLOps tools (PyTorch, SageMaker, MLFlow).
    • Hands-on experience with Kubernetes, Docker, and containerized applications.
    • AWS Certified Solutions Architect – Professional (or similar) is required.
    • Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders.
    • Strong leadership and project management skills.
    • Ability to work collaboratively in a cross-functional team environment.

Will Be a Plus:

    • Experience in the Healthcare and Biotech domains.
    • Certifications in Databricks, GCP, or Azure.
    • Experience with AWS Migration Acceleration Programs (MAP).
    • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
    • Contributions to open-source projects or active participation in the data engineering community.
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