Enterprise Data Architect

2 days ago

Pune, Maharashtra, India beBeeData Full time US$ 1,50,000 - US$ 2,00,000
Key Role: Enterprise Data Architect

We are seeking an exceptional Enterprise Data Architect to spearhead our data-driven transformation. This visionary will lead the design and implementation of cutting-edge data and AI solutions that align with business objectives.

This critical role demands a strategic thinker who can collaborate with cross-functional teams to create scalable, high-performance architectures leveraging modern technologies in data engineering, machine learning, and cloud.

  1. Design and implement end-to-end data and AI solutions addressing business challenges and optimizing decision-making.
  2. Define and implement best practices for data architecture, data governance, and AI model deployment.
  3. Collaborate with data engineers, data scientists, and business stakeholders to deliver scalable and high-impact AI-driven applications.
  4. Lead the integration of AI models with enterprise applications, ensuring seamless deployment and operational efficiency.
  5. Evaluate and recommend the latest technologies in data platforms, AI frameworks, and cloud-based analytics solutions.
  6. Ensure data security, compliance, and ethical AI implementation.
  7. Guide teams in adopting advanced analytics, AI, and machine learning models for predictive insights and automation.
Requirements:
  • 8+ years of experience in designing and implementing data and AI solutions.
  • Strong expertise in cloud platforms such as AWS, Azure, or Google Cloud.
  • Hands-on experience with big data technologies (Spark, Databricks, Snowflake, etc.).
  • Proficiency in TensorFlow, PyTorch, Scikit-learn, etc.
  • Deep understanding of data modeling, ETL processes, and data governance frameworks.
  • Experience in MLOps, model deployment, and automation.
  • Strong programming skills in Python, SQL, and Java/Scala (preferred).
  • Proficiency in Generative AI frameworks.
  • Familiarity with containerization and orchestration (Docker, Kubernetes).
Qualifications:
  • Certifications in cloud architecture, data engineering, or AI/ML.
  • Experience with generative AI.
  • Background in developing AI-driven analytics solutions for enterprises.

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