Data Architect

Company Overview

[Company information not provided.]

Job Summary

The Data Architect will be responsible for designing and implementing scalable, secure, and high-performance data architectures to support AI/ML workloads, analytics, and real-time data processing. This role plays a critical part in driving the organization's data strategy to meet analytical goals and business objectives.

Responsibilities

• Architectural Leadership Skills

  • Design and implement scalable, secure, and high-performance data architectures to support AI/ML workloads, analytics, and real-time data processing.
  • Architect data platforms that enable experimentation, model training, and deployment for classical ML, deep learning, natural language processing (NLP), and Generative AI use cases.
  • Lead the development of data lakes, feature stores, and analytical data marts optimized for both operational and research use cases.
  • Define and enforce architectural standards, data governance policies, and best practices across data science, engineering, and analytics teams.
  • Collaborate with cross-functional teams to align data architecture with business strategy and analytical goals.

• Technical Expertise & Experience

  • Translate analytical and AI/ML requirements into scalable data infrastructure and pipelines.
  • Develop and support end-to-end ML pipelines from data ingestion and feature engineering to model training, deployment, and monitoring.
  • Demonstrate hands-on experience with classical ML algorithms (e.g., regression, decision trees, ensemble methods), deep learning architectures (CNNs, RNNs, Transformers), and NLP models (BERT, GPT, T5).
  • Architect and integrate Generative AI solutions using large language models (LLMs), prompt engineering, and retrieval-augmented generation (RAG) techniques.
  • Implement DevOps practices including CI/CD pipelines, infrastructure as code, automated testing, and monitoring.
  • Ensure high standards of code quality, modularity, and reusability across data and ML pipelines.
  • Integrate modern data technologies such as Apache Spark, Apache Kafka, Delta Lake, and NoSQL databases.
  • Collaborate with data scientists to design feature stores, model registries, and scalable ML infrastructure.
  • Build and optimize data solutions on Microsoft Azure, including Azure Copilot Studio, Azure AI Foundry, Azure Data Factory, Synapse Analytics, Azure Databricks, Blob Storage, and Azure Machine Learning.

Qualifications

• 12+ years of experience in data architecture, data engineering, and data science.
• Strong programming skills in Python, SQL, and relevant scripting languages.
• Deep understanding of data modeling, ETL/ELT processes, and distributed computing.
• Hands-on experience with machine learning frameworks (e.g., TensorFlow, PyTorch), NLP libraries (e.g., spaCy, Hugging Face), and Generative AI tools (e.g., LangChain, LLMs).
• Proven experience with DevOps tools (Azure DevOps, Git, Terraform, Kubernetes).
• Expertise in Microsoft Azure preferred.
• Familiarity with MLOps practices and model lifecycle management.

Preferred Skills

• Azure certifications (e.g., Azure Solutions Architect, Azure Data Scientist Associate).
• Experience with data mesh, real-time analytics, and streaming architectures.
• Knowledge of data privacy regulations (e.g., GDPR, HIPAA).
• Exposure to AI/ML infrastructure and Generative AI safety frameworks.

Experience

• Minimum 12 years of relevant experience in data architecture, data engineering, and data science.

Environment

• Hybrid work environment with three days in-office work in Gurgaon and the remainder remote.

Salary

• Budgeted salary of INR 2.9 lakhs.

Growth Opportunities

[Career advancement opportunities not provided.]

Benefits

[Benefits information not provided.]