Data Architect

CODERS BRAIN; Gurugram District; Hybrid; INR 25,00,000 - 35,00,000; Full time

Job summary

A leading data solutions provider is seeking a Senior Data Architect in Gurugram, Haryana, to design and implement scalable data architectures for AI/ML workloads. The ideal candidate will have over 12 years of experience in data architecture and engineering, with strong programming skills in Python and SQL. This role emphasizes collaboration across teams to drive innovation and requires expertise in Microsoft Azure and ML frameworks. The position offers opportunities for leadership and strategic influence in a dynamic environment.

Qualifications

• Extensive experience in designing scalable data architectures.
• Strong programming skills in Python, SQL, and relevant scripting languages.
• Hands-on experience with ML frameworks like TensorFlow and PyTorch.

Responsibilities

• Architect data platforms and drive innovation for AI/ML infrastructure.
• Lead cross-functional teams to align data architecture with business goals.
• Collaborate with data scientists to develop end-to-end ML pipelines.

Skills

Data architecture

Data engineering

Machine Learning (ML)

Python programming

SQL

Education

12+ years of experience in relevant fields

Tools

TensorFlow

Azure Data Factory

Databricks

Kubernetes

Job description

Key Responsibilities

• 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.

Role & Responsibilities

Architect data platforms, lead cross-functional teams, drive innovation, and develop AI/ML infrastructure for advanced analytics.

Preferred Candidate Profile

Senior data architect with extensive experience in AI/ML infrastructure, expertise in Microsoft Azure, and strong leadership in cross-functional teams.