Chief Architect for Enterprise Data Solutions

2 days ago

Tiruppur, Tamil Nadu, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Unlock Business Potential through AI-Driven Solutions

Empowering organizations with the tools they need to become AI-ready is our mission. We aim to structure data efficiently across various sources, enabling AI-driven solutions that accelerate business growth and enhance cost efficiency.

We are seeking an experienced professional who can design, lead, and deliver scalable, future-proof data and AI solutions for global clients. Key Responsibilities include:

Solution Architecture

  • Engage with clients to understand business goals, technical constraints, and AI/data maturity.
  • Translate requirements into scalable solution blueprints across data, analytics, AI, and cloud.
  • Define end-to-end architecture covering ingestion, storage, processing, analytics, ML/AI, and visualization.
  • Ensure designs meet security, compliance, and governance requirements.

Data Architecture & Engineering

  • Architect modern data platforms (data lakes, lakehouses, warehouses) using tools like Databricks, Snowflake, BigQuery, Redshift, etc.
  • Design robust ETL/ELT pipelines, streaming architectures, and real-time analytics solutions.
  • Define data models, metadata management, and master data strategies.
  • Implement data governance frameworks (e.g., CDMC, DAMA DMBOK).

Ai & Mlops Enablement

  • Integrate ML/Gen AI solutions into the data platform architecture.
  • Work with Data Scientists to operationalize AI models using MLOps best practices.
  • Evaluate LLM integration, vector databases, and AI agents within enterprise architectures.

Leadership & Delivery

  • Provide technical leadership to engineering teams.
  • Review designs, code, and deployment plans for quality and scalability.
  • Work closely with client stakeholders, delivery managers, and CTO to ensure success.

Required skills and qualifications include 10+ years in data engineering, data architecture, or solution architecture roles, hands-on expertise in cloud platforms (AWS, GCP, Azure), strong knowledge of data modeling, SQL/NoSQL databases, streaming tech (Kafka, Pub/Sub, Kinesis), proven experience with Databricks, Snowflake, or equivalent modern data stack tools, knowledge of data governance, security, and compliance frameworks, familiarity with AI/ML architectures, MLOps tools (MLflow, Kubeflow), and Gen AI frameworks (LangChain, RAG pipelines), strong communication and client-facing skills.

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