The Data Architect will be responsible for designing end-to-end cloud-native data architectures on GCP, aligned to business strategy and scalability requirements. They will lead large-scale data modernization programs, including migration from on-premise or traditional platforms (such as Teradata, Oracle, Hadoop, or legacy data warehouses) to GCP services like BigQuery, Dataflow, and Pub/Sub.

The role requires close collaboration with Google account managers to leverage platform capabilities, credits, and joint go-to-market opportunities. The architect will engage regularly with senior client and internal stakeholders to translate complex technical architectures into clear business outcomes and investment decisions.

They will define data governance frameworks, data modelling standards, and best practices for cloud data platforms, and will guide and mentor engineering teams through implementation. The candidate will also be expected to contribute to pre-sales and solutioning discussions, including effort estimation and architecture proposals.

Key Skills & Knowledge Required

Cloud & Platform Expertise The candidate must have deep, hands-on expertise with GCP data services including BigQuery, Cloud Dataflow, Cloud Dataproc, Pub/Sub, Cloud Composer (Airflow), Cloud Storage, and Looker. Experience with GCP networking, IAM, and security controls relevant to data platforms is essential.

Data Modernization Proven track record of leading at least one large-scale modernization program migrating from traditional platforms such as Teradata, Oracle Exadata, Hadoop/HDFS, or on-premise data warehouses to GCP. Experience in data migration strategy, schema conversion, ETL/ELT re-platforming, and cutover planning is critical.





Data Architecture & Modelling Strong command of data warehouse design (Kimball, Inmon, Data Vault), data lake and lakehouse architectures, and modern data mesh principles. Ability to design for performance, cost efficiency, and long-term scalability.

Data Engineering Working knowledge of data pipeline design using tools such as Apache Beam, Spark, dbt, or Dataflow. Familiarity with streaming and batch processing patterns.

Stakeholder & Client Engagement Demonstrated ability to engage with C-suite and senior stakeholders translating architectural decisions into business value, managing expectations, and presenting confidently in governance forums and executive reviews.

Google Ecosystem Collaboration Prior experience working alongside Google account managers, solution engineers, or in a Google partner ecosystem is highly desirable. Ability to leverage Google's resources, best practices, and support structures as part of delivery.

Governance & Compliance Knowledge of data governance frameworks, metadata management, data lineage, and compliance requirements (GDPR, HIPAA, or relevant regional standards).

Soft Skills Strong communication and storytelling ability, executive presence, comfort with ambiguity in complex programs, and the ability to lead cross-functional teams across geographies.

Qualifications A bachelor's or master's degree in Computer Science, Engineering, or a related field is preferred. Google Skilled Data Engineer or Cloud Architect certification is strongly preferred. 15+ years of overall experience in data roles, with at least 4–5 years in cloud data architecture on GCP.

Nice to Have

Experience with multi-cloud architectures (GCP + AWS or Azure), familiarity with AI/ML pipelines on Vertex AI, and exposure to FinOps practices for cloud cost optimization.

📌 GCP Data Architect (Bengaluru)
🏢 Tenarai Technologies
📍 Bengaluru