:

Role &

Responsibilities :

- Lead the design and implementation of enterprise-scale data architecture and cloud-native data platforms.
- Define enterprise data architecture standards, principles, reference architectures and technology roadmaps.
- Design and govern Data Lakehouse / Cloud Data Platform solutions using Snowflake, Databricks, Azure and AWS.
- Drive modernization of legacy data warehouses into scalable and cost-effective cloud data platforms.
- Define conceptual, logical and physical data models using Kimball, Data Vault, 3NF or hybrid approaches.
- Establish Data Governance, Data Quality, Metadata, Data Lineage, Data Catalog and MDM frameworks.
- Define and implement Data Product operating models, including ownership, lifecycle, roadmap, KPIs and adoption metrics.
- Design batch, real-time, streaming and event-driven data integration architectures.
- Provide architecture guidance across SQL, Python, PySpark, ETL/ELT and Kafka/streaming technologies.
- Provide secondary architecture support for AI/ML, MLOps, feature engineering, model deployment and monitoring.
- Review technical designs for scalability, security, resilience, maintainability, performance and cost.
- Lead architecture reviews and provide technical direction to Data Engineers, Architects and delivery teams.
- Conduct architecture workshops with business, security, governance and engineering stakeholders.
- Evaluate technology options,



identify risks and communicate architecture trade-offs to senior management.
- Create architecture blueprints, decision records, governance standards and modernization roadmaps.

Preferred Candidate Profile :

- 12 years of experience in Enterprise Data Architecture with strong hands-on architecture ownership.
- Minimum 5 years of experience with cloud-native data platforms.
- Strong experience with Snowflake, Databricks, Azure and AWS data services.
- Proven experience designing enterprise data platforms, Data Lakehouse and data modernization solutions.
- Strong knowledge of Data Governance, Data Quality, Metadata, Lineage, Data Catalog and MDM.
- Hands-on experience with Data Product management, including ownership, lifecycle, roadmap, KPIs and adoption metrics.
- Robust understanding of Kimball, Data Vault, Dimensional and 3NF data modelling.
- Strong technical knowledge of SQL, Python, PySpark, ETL/ELT and Kafka/Streaming.
- Working knowledge of AI/ML architecture and MLOps.
- Demonstrated ability to translate business requirements into scalable, governed and reusable data solutions.
- Strong stakeholder management and executive-level communication skills.
- Experience guiding engineering teams and governing implementation quality.
- Experience in large enterprise / multinational environments is preferred.
- Immediate availability and willingness to work 3 days per week from Electronic City, Bangalore preferred.

📌 Senior Data Architect - Snowflake (India)
🏢 Sunovaa Tech
📍 India