Role : Principal Data Architect - Data & AI Platforms (GCP)

Location : Pune / Noida / Jaipur / Bangalore (Hybrid)

Experience : 14+ Years

Preferred Background : IT Product Companies

Role Overview :

We are seeking an experienced Principal Data Architect to lead the design and development of scalable, enterprise-grade Data and AI platforms, with a GCP-first architecture.

In this role, you will be responsible for defining end-to-end enterprise data architecture spanning data ingestion, storage, transformation, governance, analytics, and ML enablement.

You will collaborate closely with business stakeholders, data engineering teams, and platform leaders to translate strategic objectives into modern, high-performance data ecosystems.

Key Responsibilities :

Enterprise Data & AI Architecture :

- Define end-to-end data platform architecture supporting batch, streaming, and CDC pipelines.

- Architect scalable Data Warehouse and Lakehouse solutions on BigQuery.

- Establish reference architectures across OLTP systems, NoSQL databases, Data Warehouses, ML platforms, and BI tools.

- Drive serverless-first and multi-tenant architecture principles on GCP.

Data Engineering & Streaming :

- Design real-time and event-driven data pipelines using Pub/Sub, Kafka, Dataflow, and Apache Beam.

- Standardize Change Data Capture (CDC) architectures using Datastream and Debezium.

- Implement Medallion / Lakehouse architecture (Bronze, Silver, Gold layers).

- Ensure strong CI/CD, testing frameworks, versioning, and reliability for data pipelines.

Data Modeling & Storage :

- Design and implement enterprise-scale Data Warehouses on BigQuery.

- Apply Kimball, Data Vault, and Inmon data modeling methodologies.

- Optimize partitioning, clustering, performance, and cost efficiency.

- Guide architecture decisions around NoSQL systems such as Bigtable, MongoDB, Redis, and Neo4j.

Data Governance, Security & Observability :

- Implement Data Mesh principles and domain-driven data products.

- Establish data contracts, quality frameworks, and lineage tracking.

- Ensure regulatory compliance through SOX, DLP policies, IAM, encryption, and RBAC/ABAC models.

- Define observability standards, monitoring frameworks, SLAs/SLOs, and cost governance.

AI / ML Enablement :

- Architect feature stores and ML pipelines for scalable ML workflows.

- Enable real-time analytics, vector search, and RAG-based AI architectures.

- Ensure model observability, reproducibility, and governance frameworks.

Leadership & Strategy :

- Mentor and guide senior engineers, architects, and platform teams.

- Lead architecture reviews and platform standardization initiatives.

- Drive the enterprise data strategy, innovation roadmap, and technology adoption.

Required Skills & Expertise :

- Strong expertise in Google Cloud Platform (GCP) - BigQuery, GCS, Pub/Sub, Dataflow, Composer/Airflow.

- Hands-on experience with Kafka, real-time streaming, and CDC architectures.

- Advanced knowledge of data modeling and enterprise data warehouse design.

- Experience with Lakehouse technologies such as Iceberg, Delta Lake, or Hudi.

- Strong programming skills in SQL and Python (Java/Scala is a plus).

- Experience with Terraform, CI/CD pipelines, and infrastructure automation.

- Deep understanding of enterprise data governance, security, and compliance frameworks