Description :

About Auxo AI :

We are an AI-first company that accelerates our clients transformative journeys as they embrace and integrate AI to drive their business innovation, growth and address challenges. We help AI inside the fabric of their ecosystem through unique blend of advisory, decision sciences and engineering. For details visit- auxoai.com

Company Size : Startup / Small Enterprise

Working Days : 5 days/week

Role & Responsibilities :

- Strong Databricks / AWS Data Architect profile

- Minimum 5+ years of experience in Data Architecture / Data Engineering, with exposure in enterprise-scale data platform modernization initiatives

- Minimum 3+ years of deep hands-on experience in Databricks-based lakehouse architecture on AWS, including large-scale data platform implementations

- Strong expertise in Databricks ecosystem including Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables, and MLflow with focus on performance optimization and security

- Strong experience with AWS data services including S3, Glue, EMR, Lambda, Redshift, Athena, Lake Formation, and DMS, with strong understanding of cloud-native architecture patterns

- Proven experience designing and implementing Medallion (Bronze/Silver/Gold) architecture, scalable data models (Dimensional/Data Vault), and enterprise lakehouse platforms supporting batch and real-time processing

- Hands-on experience building scalable ingestion frameworks including batch, streaming, and CDC pipelines using tools like Kafka, Kinesis, Spark, or similar technologies

- Proven experience implementing CI/CD pipelines for data platforms, including infrastructure as code, automated deployments, and environment management

- Hands-on experience enabling data platforms for AI/ML and Generative AI use cases, including feature stores, vector storage, and secure data access patterns

- Experience with orchestration tools such as Apache Airflow or MWAA and designing integration layers for analytics, BI, and AI consumption

- AWS / Databricks / Snowflake certifications; experience with Snowflake alongside Databricks; exposure to MDM, data quality frameworks, and enterprise metadata tools