HCLTech
HCLTech is looking for a highly talented and self-motivated Data & AI Architect to join it in advancing the technological world through innovation and creativity.
Job Title: Data & AI Architect
Job ID: 1506126
Position Type: Full Tid)
Primary Skill
Data architecture , cloud ( Azure / GCP / AWS ) , Databricks / snowflake , Data modelling, exposure to agentic Ai , GenAI
Secondary Skill
Secondary Skill
Mandatory Skill
Pyspark, advance SQL, ETL , data- warehouse
Must-Have Skills
Pyspark, advance SQL, ETL , data- warehousing
Good-to-Have Skill
Good-to-Have Skill
Required Skills & Experience
- 14+ years of overall experience in data architecture, data engineering, or related roles.
- 8+ years of hands-on experience with cloud data platforms (AWS, Azure, and/or GCP) — architecture, design, and implementation.
- Hands-on experience with Databricks and/or Snowflake for large-scale data engineering, analytics, and lakehouse workloads.
- Proven hands-on experience with AI/ML solutions, including LLM-based application development and AI agent design/development.
- Strong grounding in data modelling (conceptual, logical, physical), data warehousing, and modern lakehouse architectures.
- Experience with data integration tools/ETL-ELT frameworks (e.g., Informatica, dbt, Talend, Glue, ADF).
- Working knowledge of vector databases (e.g., Pinecone, FAISS, pgvector) and RAG architectures.
- Experience with agent frameworks/protocols (e.g., LangChain, LangGraph, AutoGen, MCP) is highly desirable.
- Proficiency in SQL and at least one programming language (Python preferred) for prototyping and integration work.
- Solid understanding of data governance, security, and privacy/compliance requirements (e.g., GDPR).
- Strong stakeholder management, communication, and technical leadership skills.
Preferred Qualifications
- Cloud certifications (AWS/Azure/GCP Solutions Architect or Data Engineer).
- Databricks (e.g., Databricks Certified Data Engineer) and/or Snowflake (e.g., SnowPro Core) certifications.
- Experience in a specific domain relevant to the business (e.g., banking, financial services, insurance).
- Exposure to MLOps/LLMOps tooling (MLflow, Vertex AI, SageMaker, Azure AI Studio).
- Experience presenting architecture and AI strategy to senior/executive stakeholders.
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