Data Architect

KEY RESPONSIBILITIES

• Data Architecture & Strategy

• Define and implement

  data platform blueprints

  across cloud and hybrid environments.
• Design architectures for

  data lakes, warehouses, and real-time streaming pipelines

  .
• Ensure alignment with

  business goals, AI readiness, and compliance requirements

  .

• Enterprise Data Modeling & Governance

• Establish standards for

  data modeling, lineage, quality, and master data management

  .
• Implement

  governance frameworks

  to meet enterprise and regulatory needs (GDPR, SOC2, HIPAA).

• AI & Analytics Enablement

• Architect

  data pipelines

  that feed into

  LLMs, RAG systems, and Vision AI workflows

  .
• Collaborate with AI/ML teams to design

  high-quality, labeled, and observable datasets

  .

• Technology & Integration

• Define reference architectures for

  ETL/ELT, vector databases, and knowledge graph integration

  .
• Evaluate and select technologies across

  AWS, Azure, GCP, and open-source data ecosystems

  .

• Leadership & Collaboration

• Mentor

  data engineers and platform engineers

  on best practices.
• Partner with

  Product, AgentOps, and Security teams

  to ensure reliable, compliant, and cost-optimized data systems.

SKILLS & QUALIFICATIONS

Must-Have

• 812 years in

  data engineering, architecture, or analytics platform leadership

  .
• Proven expertise in

  data modeling, ETL/ELT pipelines, and distributed data systems

  .
• Hands-on with

  big data and analytics frameworks

  (Spark, Kafka, Delta Lake, Databricks).
• Strong knowledge of

  cloud-native data ecosystems (AWS Redshift/Glue, Azure Synapse/Data Factory, GCP BigQuery/Dataflow)

  .
• Proficiency in

  SQL, Python, and data orchestration frameworks (Airflow, dbt)

  .
• Deep understanding of

  data governance, compliance, and security best practices

  .

Good-to-Have

• Experience with

  vector databases (Pinecone, Weaviate, FAISS) and knowledge graphs

  .
• Familiarity with

  LLM/AI data pipelines and agentic system data needs

  .
• Certifications in AWS/Azure/GCP data engineering or architecture.
• Industry exposure to

  BFSI, GRC, SOC, or regulated enterprise environments

  .