We are looking for an experienced GCP Data Architect to design, build, and optimize scalable cloud-based data platforms on Google Cloud Platform (GCP).

The ideal candidate should have expertise in modern data architecture, cloud-native data engineering, and analytics solutions, with the ability to define enterprise-wide data strategies and deliver high-performance, secure, and cost-efficient data ecosystems.

Key Responsibilities:

- Design and implement scalable, secure, and highly available data architectures on Google Cloud Platform.

- Build enterprise data lakes, data warehouses, and real-time data processing solutions.

- Architect end-to-end ETL/ELT pipelines for structured and unstructured data.

- Define data models, governance frameworks, metadata management, and data quality standards.

- Collaborate with business stakeholders, data engineers, analysts, and application teams to understand data requirements.

- Optimize data storage, processing performance, and cloud infrastructure costs.

- Implement security best practices, encryption, IAM policies, and compliance controls.

- Design batch and streaming data solutions using modern cloud technologies.

- Drive cloud migration initiatives from on-premise or other cloud platforms to GCP.

- Mentor engineering teams and establish architecture best practices and coding standards.

Required Skills :

- Strong expertise in Google Cloud Platform (GCP)

- BigQuery

- Cloud Storage

- Cloud Composer (Apache Airflow)

- Dataflow

- Dataproc

- Pub/Sub

- Cloud Functions

- Cloud Run

- Vertex AI (basic understanding for data integration)

- SQL and advanced data modeling

- Python or Java for data processing

- Apache Spark

- ETL/ELT architecture

- Data Warehousing

- Data Lake Architecture

- API Integration

- IAM, Security, and Governance

- CI/CD for data platforms

- Git and Infrastructure as Code (Terraform preferred)

Preferred Qualifications :

- Hands-on experience with enterprise-scale cloud data platforms.

- Strong understanding of distributed data processing and analytics.

- Experience with real-time data ingestion and event-driven architectures.

- Knowledge of performance tuning, partitioning, clustering, and query optimization.

- Experience integrating BI and reporting tools such as Looker or Power BI.

- Familiarity with Agile/Scrum development methodologies.

- GCP Professional Data Engineer or Professional Cloud Architect certification is preferred.

Good to Have :

- Kafka

- dbt

- Docker

- Kubernetes (GKE)

- Snowflake integration with GCP

- Data governance tools such as Dataplex or Collibra

- Experience in Finance, Retail, Healthcare, or Telecom domains