We are hiring a Data Architect to lead a strategic enterprise data modernization initiative for platform using Medallion architecture AWS Databricks. The role will define target-state architecture, establish enterprise data governance frameworks, implement CI/CD best practices for data platforms, and build GenAI-ready data foundations that enable advanced analytics, machine learning, and secure enterprise data access.
You will be responsible for architecting scalable cloud-native data ecosystems, designing governed data models, and enabling real-time and batch data processing capabilities. This role requires deep ownership of architecture standards, platform performance, and cross-functional alignment across engineering, analytics, and data science teams to ensure consistent, secure, and high-performance data consumption across enterprise use cases.
Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)
Responsibilities -
- Lead enterprise-scale implementation of data warehouse data platforms on Databricks and Snowflake environments.
- Design and implement Medallion (Bronze/Silver/Gold) architecture and scalable enterprise data models.
- Establish data modeling standards (dimensional, data vault, lakehouse patterns) and ensure best practices across projects
- Establish enterprise data governance frameworks including cataloging, lineage, stewardship, and compliance using Atlan.
- Define and implement CI/CD pipelines for infrastructure and data platform deployments
- Design data architectures that support AI/ML and Generative AI workloads including vector storage, feature layers, and secure access patterns.
- Build scalable ingestion frameworks supporting batch, streaming, and CDC pipelines.
- Architect secure, high-performance data integration layers for analytics, BI, and AI consumption.
- Develop target-state architecture blueprints and enforce data standards, governance, and best practices across teams.
- Collaborate with engineering, analytics, and data science teams to ensure platform alignment and scalability.
- Engage with clients as a trusted advisor, driving data strategy, roadmap definition, and identifying opportunities for expansion.
Requirements
- Minimum 10 years of experience in Data & Analytics Architecture with proven leadership in large-scale enterprise data modernization initiatives
- Strong understanding of batch, streaming, real-time, and near real-time data architectures
- Proven experience implementing enterprise Data Governance frameworks and tool
- Hands-on experience enabling AI/ML and Generative AI data pipelines.
- Deep expertise in data domains including Data Warehousing, Data Modeling (Dimensional, Data Vault), MDM, Data Quality, Metadata Management, and Data Catalog implementation
- Advanced Databricks experience including architecture design, optimization, and security; including hands-on experience with Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables, MLflow and integration with cloud services (AWS/Azure)
- Strong hands-on experience with AWS data ecosystem (S3, Glue, EMR, Lambda, Redshift, Lake Formation, Athena, DMS, etc.)
- Experience with real-time/streaming technologies (Kafka, Kinesis, or similar)
- Familiarity with orchestration tools such as Apache Airflow or MWAA
- Experience implementing CI/CD pipelines for data platforms
- AWS, Databricks and/or Snowflake certifications preferred
Skills Required
- Minimum 10 years of experience in Data and Analytics Architecture
- Leadership experience in large-scale enterprise data modernization initiatives
- Strong understanding of batch, streaming, real-time, and near-real-time data architectures
- Experience implementing enterprise data governance frameworks and tools
- Hands-on experience enabling AI, machine learning, and Generative AI data pipelines
- Expertise in data warehousing, dimensional and Data Vault modeling, MDM, data quality, metadata management, and data catalogs
- Advanced Databricks experience, including architecture, optimization, security, Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables, and MLflow
- Experience integrating Databricks with AWS or Azure cloud services
- Strong hands-on experience with the AWS data ecosystem, including S3, Glue, EMR, Lambda, Redshift, Lake Formation, Athena, and DMS
- Experience with real-time and streaming technologies such as Kafka or Kinesis
- Familiarity with Apache Airflow or MWAA
- Experience implementing CI/CD pipelines for data platforms
- AWS, Databricks, and/or Snowflake certifications
- Ability to join immediately or within two weeks
What We Do
AuxoAI partners with enterprise leaders to build AI systems, enabling the creation of AI-first enterprises by moving from AI strategy to production-grade deployed systems in weeks.
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