GCP Data Architect

Tekskills; Pune District; Hybrid; INR 1,800,000 - 3,200,000; Full time

Job summary

Senior Data Architect at Tekskills will lead cloud data engineering initiatives across GCP, AWS, and Azure. Candidates should have 10–15 years of experience designing scalable data solutions and modern data architectures.

Responsibilities include shaping end-to-end data pipelines using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, and Looker. Develop data lake, warehouse, and lakehouse architectures on GCP; Databricks experience on AWS/Azure is a plus.

Qualifications

• Experience architecting solutions in Cloud Data Engineering platforms (GCP/AWS/Azure).
• Design end-to-end data architectures on GCP using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, Looker.
• Develop data lake, data warehouse, and lakehouse architectures on GCP; experience with Databricks in AWS/Azure is a plus.
• Create logical and physical data models, data flow diagrams, integration patterns, and reference architectures.
• Architect scalable ETL/ELT pipelines using Dataflow (Apache Beam), Dataproc (Spark), and/or Cloud Composer orchestrations.
• Lead cloud-native modernization— migration from legacy platforms to GCP.

Skills

GCP

BigQuery

Dataflow

Dataproc

Pub/Sub

Looker

Data lake

Data warehouse

Lakehouse

ETL/ELT

Apache Beam

Spark

Cloud Storage

Cloud Composer

Data modeling

Tools

Databricks

Apache Beam

Spark

Job description

Role: Senior Data Architect

Total Year of experience: 10-15 years

Job Description:

• Experience architecting solutions in Cloud Data Engineering platform (eg: GCP, AWS, Azure)
• Design endtoend data architectures on GCP leveraging BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, and Looker.
• Develop modern data lake, data warehouse, and lakehouse architectures using best practices and wellarchitected frameworks in GCP and prefer to have experience in AWS, Azure & Databricks
• Create logical and physical data models, data flow diagrams, integration patterns, and reference architectures.
• Architect scalable ETL/ELT pipelines using Dataflow (Apache Beam), Dataproc (Spark), and/or Cloud Composer orchestrations.
• Lead cloud-native modernization initiatives: migration from legacy platforms to GCP