Data Architect

Location: Gurugram, Work From Office

Notice period: Immediate to 30days

Job Title: Data Architect – AI/ML, Data Engineering & Analytics

Role Overview

We are seeking a visionary and hands-on Data Architect with 14+ years of experience in designing and implementing scalable data solutions across Data Science, Data Engineering, and Analytics domains. The ideal candidate will have a deep understanding of AI/ML techniques, including Classical Machine Learning, Deep Learning, Natural Language Processing (NLP), and Generative AI (GenAI), along with strong architectural and cloud expertise. This role requires the ability to lead multiple technical projects in parallel, enforce coding and DevOps standards, and architect modern data platforms—preferably on Microsoft Azure.

Key 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, NLP, and GenAI 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.- 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 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 Spark, 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.

Required 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 ML frameworks (e.g., TensorFlow, PyTorch), NLP libraries (e.g., spaCy, Hugging Face), and GenAI tools (e.g., LangChain, LLMs).- Proven experience with DevOps tools (ADO, 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 Assoc.).
- 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 GenAI safety frameworks.

Soft Skills

- Excellent communication and stakeholder engagement skills.
- Ability to lead cross-functional teams and manage competing priorities.- Strategic thinking with a hands-on approach to execution.- Passion for innovation, continuous learning, and mentoring.

Job Types: Full-time, Permanent

Pay: ₹2,200,000.00 - ₹3,000,000.00 per year

Ability to commute/relocate:

• Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required)

Application Question(s):

• Notice period
• Current CTC
• Expected CTC

Experience:

• with ML frameworks (e.g., TensorFlow, PyTorch): 3 years (Required)
• NLP libraries (e.g., spaCy, Hugging Face): 3 years (Required)
• GenAI tools (e.g., LangChain, LLMs): 2 years (Required)
• DevOps tools (ADO, Git, Terraform, Kubernetes).: 2 years (Required)
• data architecture & data engineering: 10 years (Required)
• Python, SQL, and relevant scripting languages: 5 years (Required)

Work Location: In person