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Cloud Data Architect (With AI experience)

7 hours, 2 minutes ago
India
Full-time
Lead
Data Architect
Artificial Intelligence and Machine Learning
Apache Spark AWS Azure Databricks Docker FastAPI GitHub Actions Grafana Hugging Face Kafka Kubernetes MLflow MLOps Neo4j OpenSearch Python PyTorch Snowflake SQL Terraform
Apply Now
3Pillar Global

3Pillar Global

3Pillar Global is an innovative product development company that builds breakthrough software products to power digital businesses. They offer a range of services including product strategy, management, user experience design, and software engineering ...

Internet Software & Services
1K-5K
Founded 2006
$26M raised
View All Jobs 49

Description

  • Architect and own the enterprise AI data platform as the unified, governed source of truth for all AI systems.
  • Design multi-domain data models and cloud-native architectures using lakehouse, data mesh, and event-driven patterns.
  • Own the full data stack across streaming, batch processing, cloud storage, compute, and data quality and metadata management.
  • Modernize legacy ETL and batch data warehouse pipelines into cloud-native, AI-ready architectures.
  • Design and maintain semantic layers, ontologies, knowledge graphs, and domain taxonomies for AI context and reasoning.
  • Build retrieval infrastructure for RAG applications, including embedding pipelines, vector stores, chunking, and hybrid search.
  • Own ML and LLMOps data infrastructure, including training data curation, feature engineering, model registry, evaluation, and monitoring.
  • Build CI/CD pipelines and production controls for AI systems, including validation, quality gates, deployment automation, and rollback.
  • Design governance and security controls for human and agent access, including RBAC, masking, encryption, and audit logging.
  • Define reference architectures, engineering standards, and design reviews for AI-ready data platform integration.

Requirements

  • 15+ years of hands-on data engineering and architecture experience.
  • 3–5+ years building production AI/ML and LLM-era data infrastructure.
  • Proven experience designing enterprise-scale AI data platforms that support multiple AI consumers.
  • Deep expertise in lakehouse and data mesh architectures, including Databricks, Delta Lake, PySpark, Kafka, Spark Structured Streaming, AWS, and Azure.
  • Hands-on production experience with vector stores, semantic models, knowledge graphs, and retrieval infrastructure.
  • Working knowledge of LLMOps, including model serving pipelines, MLflow, CI/CD for AI, automated evaluation, and production monitoring.
  • Strong background in data governance, security, and compliance in regulated industries such as financial services, payments, cybersecurity, or healthcare.
  • Experience defining data access controls for AI agents and automated systems.
  • Primary technical skills include Python, SQL, PySpark, Kafka, Databricks, Delta Lake, Snowflake, AWS services, Docker, Kubernetes, Terraform, GitHub Actions, LangChain, LlamaIndex, LLM APIs, vector databases, and Neo4j.
  • Secondary skills include FastAPI, observability tools such as CloudWatch or Grafana, and data lineage/metadata management platforms.

Interested in this position?

Apply directly on the company website

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