Dremio Data Architect

2 weeks ago


Bangalore, India AuxoAI Full time

AuxoAI partners with leading enterprises to modernize their data ecosystems using cloud-native and AI-ready architectures. We are seeking an experienced Dremio Data Architect to lead the design and optimization of our modern data lakehouse platform — enabling governed, high-performance analytics across structured and unstructured data. Role Overview You will be responsible for architecting, implementing, and optimizing Dremio-based data lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments. Responsibilities: - Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem). - Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads. - Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns. - Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS). - Establish best practices for data security, lineage, and access control aligned with enterprise governance policies. - Support self-service analytics by enabling governed data products and semantic layers. - Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling. - Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data. Requirements: - Bachelor's or Master's in Computer Science, Information Systems, or related field. - 10+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms. - Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena). - Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning. - Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.). - Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC). - Excellent problem-solving, documentation, and stakeholder communication skills. Preferred: - Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview). - Exposure to Snowflake, Databricks, or BigQuery environments. - Experience in high-tech, manufacturing, or enterprise data modernization programs.


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