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Data Architect (Dremio Lakehouse)
AI-First Company
Data Architect (Dremio Lakehouse)
AI-First Company's logo

Data Architect (Dremio Lakehouse)

at AI-First Company

Agency job
5 - 17 yrs
₹30L - ₹45L / yr
Bengaluru (Bangalore), Mumbai, Hyderabad, Gurugram
Skills
Data engineering
Data architecture
SQL
Data modeling
GCS
JDBC
Apache Airflow
Data Transformation Tool (DBT)
Apache Kafka
Spark
Architecture
Data governance
RBAC
skill iconData Science
Tableau
PowerBI
Looker
databricks
skill iconAmazon Web Services (AWS)
Windows Azure
Microsoft Windows Azure
SQL Azure
RESTful APIs
Data security
Meta-data management
ADF
Apache Synapse
Data archiving
Data warehouse architecture
Amazon S3
AWS Lambda
Amazon Redshift
PySpark
Apache Spark
SPARQL
CI/CD
Dimensional modeling
Symantec Enterprise Vault
Glue semantics
Semantics
skill iconData Analytics
Data-flow analysis
Big Data
Core Data
Data masking
skill iconGitHub
DevOps
Terraform
Informatica PowerCenter
Google Cloud Platform (GCP)
skill iconGoogle Analytics
dremio

ROLES AND 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.


  • 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.


IDEAL CANDIDATE:

  • Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
  • 5+ 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.
Read more
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Full Stack Developer - Averlon
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