Senior Data Architect

Sunovaa Tech Pvt. Ltd.; Bengaluru; Hybrid; INR 3,500,000 - 7,500,000; Full time

Job summary

Sunovaa Tech Pvt. Ltd. in Bengaluru seeks an expert Enterprise Data Architect to lead design and governance of data platforms, driving modernization and cloud adoption across Snowflake, Databricks, Azure and AWS.

The role requires deep experience in data modeling, governance frameworks and data product management, with executive-level communication and collaboration with security and governance teams. Immediate availability is preferred, with on-site presence at Electronic City, Bengaluru.

Qualifications

• 15+ years of experience in Enterprise Data Architecture with hands-on 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, KPIs and adoption metrics.
• Strong 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.

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.

Skills

Enterprise data architecture

Cloud-native data platforms

Snowflake

Databricks

Azure

AWS

Data governance

Data quality

Metadata

Data lineage

Data catalog

MDM

Data product management

Kimball

Data Vault

3NF data modelling

SQL

Python

PySpark

ETL/ELT

Kafka/Streaming

AI/ML architecture

MLOps

Executive-level communication

Tools

Snowflake

Databricks

Azure

AWS

Kafka

PySpark

SQL

Python

Job description

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

• 15+ 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.


• Strong 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.