Data And AI Architect Expert

Data & AI Architect

Key Responsibilities

1. Architecture & Solution Design

• Design end-to-end

  Data, Analytics & AI architectures

  across cloud and on-prem environments.
• Lead

  data platform modernization

  , data lake/lakehouse, and MLOps architecture initiatives.
• Define scalable cloud-native architectures using

  Azure / AWS / GCP

  .
• Build reference architectures, solution frameworks, and reusable templates.
• Ensure architectures meet performance, security, and compliance standards.

2. Pre-Sales & Client Engagement

• Participate in RFP/RFI responses, solutioning, and effort estimation.
• Conduct client workshops, requirement discovery sessions, and technical presentations.
• Develop

  solution proposals

  , presentations, and business value narratives.
• Support sales teams in positioning Data & AI offerings to enterprise clients.
• Build and showcase PoCs, demos, architecture documents, and value assessments.

3. Data Engineering & AI/ML Expertise

• Architect and guide teams on

  data pipelines, ETL/ELT, and real-time streaming

  .
• Strong understanding of

  ML lifecycle

  , model deployment, CI/CD, MLOps.
• Ability to design AI solutions such as

  GenAI pipelines, RAG, LLM fine-tuning, vector databases

  , etc.
• Knowledge of Big Data technologies (Spark, Databricks, Hadoop, Kafka).

4. Stakeholder Management

• Act as a technical advisor to customers and internal leadership.
• Collaborate with cross-functional teams—data engineers, scientists, cloud architects, sales, and delivery.
• Ensure seamless handover from pre-sales to delivery teams.

Required Skills & Experience

Technical Skills

• 10–15+ years of experience in Data Engineering, Analytics, and Cloud Architecture.
• Strong knowledge in one or more cloud platforms:

• Azure

  (preferred): ADF, Databricks, Synapse, Purview, Fabric, Azure OpenAI

• AWS

  : Redshift, Glue, S3, SageMaker, Bedrock

• GCP

  : BigQuery, Vertex AI
• Expertise in:
• Data Lake, Data Warehouse, Lakehouse, Streaming
• Databricks / Spark
• GenAI (LLMs, RAG, Vector DBs like Pinecone, FAISS, Chroma)
• MLOps (MLflow, Azure ML, Kubeflow)
• API design & integration for AI applications
• Strong command over Python, SQL, and ETL/ELT frameworks.

Pre-Sales Competencies

• Experience in

  RFP/RFI solutioning

  and proposal writing.
• Ability to articulate business value, ROI, and solution differentiators.
• Experience conducting

  client demos, workshops, PoCs

  , and architecture presentations.
• Strong communication and presentation skills.