Role & Responsibilities
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.
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Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
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Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
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Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
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Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
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Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
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Support self-service analytics by enabling governed data products and semantic layers.
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Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
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Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.
Ideal Candidate
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Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
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5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
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Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
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Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
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Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
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Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
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Excellent problem-solving, documentation, and stakeholder communication skills.
Preferred
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Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
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Exposure to Snowflake, Databricks, or BigQuery environments.
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Experience in high-tech, manufacturing, or enterprise data modernization programs.
Skills: dremio,modeling,enterprise,data,access control,design,cloud,storage,enterprise data,architecture