Auxo AI - Dremio Data Architect - SQL/Kafka

10 years

0 Lacs

Posted:3 days ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Notice period : Immediate to 30days

Key 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 :
  • Bachelors or Masters 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.
(ref:hirist.tech)

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