Global Data Architect

Naukri Assist; Gurugram District; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

Naukri Assist seeks a seasoned Data Architect to lead data warehouse design, cloud platform implementation, and governance across multiple environments. The role involves defining data models, crafting scalable architectures, and ensuring security and compliance within cross-functional teams.

The candidate should have extensive SQL proficiency, hands-on ETL/ELT experience, and strong communication skills to articulate architecture and recommendations across stakeholders.

Qualifications

• 12+ years of IT experience with data warehouse / database projects.
• Expertise in cloud data platforms and databases like Snowflake, Redshift, BigQuery, Databricks, data catalog, MDM.
• Proficient in writing SQL and database procedures.
• Designing solution architecture considering integration points, data flows, and security.
• Proficient in Data Modelling - conceptual, logical, physical modeling.
• Document architecture-related work thoroughly.
• Hands-on experience in data storage, ETL/ELT and data analytics tools e.g. Talend, dbt, Attunity, Golden Gate, Fivetran, APIs, Tableau, Power BI, Alteryx.
• Experience in Data Warehousing design / development and BI / Analytical systems.
• Experience working with Agile methodologies.
• Strong hands-on experience with data and analytics architecture, solution design, and engineering.
• Experience with Cloud Big Data technologies AWS, Azure, GCP, Snowflake, BigQuery, Databricks.
• Experience with Python would be preferable.
• Experience with agile methodologies (Scrum, Kanban) and cross-functional teams.
• Review databases and data models across systems and propose enhancements.
• Excellent written, oral communication and presentation skills.

Skills

Data warehousing

SQL scripting

Cloud data platforms

Data modelling

Architectural design

GenAI integration

Python scripting

Agile methodologies

Security/compliance

Data governance

Tools

Snowflake

Redshift

BigQuery

Databricks

Talend

dbt

Tableau

Power BI

Fivetran

LangChain

Job description

Essential Experience & Job Requirements

• 12+ years of IT experience with major focus on data warehouse / database related projects.
• Expertise in cloud data platforms and databases like Snowflake, Redshift, BigQuery, Databricks, data catalog, MDM etc.
• Expertise in writing SQL and database procedures.
• Proficient in designing solution architecture factoring in all integration points, data flows and
  security/vulnerabilities.
• Proficient in Data Modelling - conceptual, logical, and physical modelling.
• Proficient in documenting all the architecture related work performed.
• Hands on experience in data storage, ETL / ELT and data analytics tools and technologies e.g.,
  Talend, dbt, Attunity, Golden Gate, Fivetran, APIs, Tableau, Power BI, Alteryx etc.
• Experienced in Data Warehousing design / development and BI / Analytical systems.
• Experience working projects using Agile methodologies.
• Strong hands-on experience with data and analytics data architecture, solution design, and
  engineering experience.
• Experience with Cloud Big Data technologies such as AWS, Azure, GCP, Snowflake, BigQuery, and Databricks.
• Experience with Python would be preferable.
• Experience working with agile methodologies (Scrum, Kanban) and Meta Scrum with cross-functional teams (Product Owners, Scrum Master, Architects, and data SMEs).
• Review existing databases, data architecture, data models across multiple systems and propose
  architecture enhancements for cross compatibility and target systems.
• Excellent written, oral communication and presentation skills to present architecture, features, and solution recommendations.

GOOD TO HAVE: GENAI, AGENTIC AI & EMERGING ARCHITECTURE

CAPABILITIES

• Hands-on experience designing, evaluating, or supporting GenAI / LLM-enabled solutions, including
  proofs of concept and production-oriented architecture patterns.
• Understanding of Agentic AI concepts, multi-step orchestration, tool-using AI agents, and human-in
  the-loop design considerations.
• Experience with retrieval architectures such as RAG, GraphRAG, hybrid search, semantic search,
  and context-grounding approaches for enterprise use cases.
• Familiarity with vector databases, knowledge graphs, metadata-rich knowledge stores, and
  enterprise knowledge base design for AI applications.
• Exposure to AI application frameworks and orchestration tools such as LangChain and LangGraph.
• Awareness of agent-to-agent interaction patterns, A2A concepts, model context management (MCP), and emerging interoperability standards such as MCP.
• Experience evaluating data readiness for GenAI use cases, including chunking strategy, retrieval quality, data lineage, access controls, and content governance.
• Understanding of prompt design, evaluation approaches, observability, guardrails, safety, and
  responsible AI controls in enterprise environments.
• Ability to partner with product, engineering, architecture, and governance teams to shape scalable GenAI-enabled data products and platforms.