
Review Criteria
- Strong Dremio / Lakehouse Data Architect profile
- 5+ years of experience in Data Architecture / Data Engineering, with minimum 3+ years hands-on in Dremio
- Strong expertise in SQL optimization, data modeling, query performance tuning, and designing analytical schemas for large-scale systems
- Deep experience with cloud object storage (S3 / ADLS / GCS) and file formats such as Parquet, Delta, Iceberg along with distributed query planning concepts
- Hands-on experience integrating data via APIs, JDBC, Delta/Parquet, object storage, and coordinating with data engineering pipelines (Airflow, DBT, Kafka, Spark, etc.)
- Proven experience designing and implementing lakehouse architecture including ingestion, curation, semantic modeling, reflections/caching optimization, and enabling governed analytics
- Strong understanding of data governance, lineage, RBAC-based access control, and enterprise security best practices
- Excellent communication skills with ability to work closely with BI, data science, and engineering teams; strong documentation discipline
- Candidates must come from enterprise data modernization, cloud-native, or analytics-driven companies
Preferred
- Preferred (Nice-to-have) – Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments
Job Specific Criteria
- CV Attachment is mandatory
- How many years of experience you have with Dremio?
- Which is your preferred job location (Mumbai / Bengaluru / Hyderabad / Gurgaon)?
- Are you okay with 3 Days WFO?
- Virtual Interview requires video to be on, are you okay with it?
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.
- 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.

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We are actively looking for backend software engineers who are passionate about building cutting-edge systems that work on the latest tech stack (Python, Django) but also help save lives. You’ll have the opportunity to learn and lead the development of several AI-enabled products and solutions within the company that are geared to help accelerate the development of new cures and to reduce the inefficiencies in how healthcare information is managed.
Key Responsibilities:
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Required Skills and Qualifications:
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Qrata is a talent startup that partners with fast-moving digital companies globally to scale their teams. Since 2016,\Ve have served over 100 funded startups ( top brands. some unicorns tool) and hire teams in the spaces of engineering. growth, design and product Our mission is to be the top curated talent marketplace while fostering a collaborative, diverse, and inclusive \ workplace.
Qrata matches top talent with global career opportunities from the world’s leading digital companies including some of the world’s fastest-growing startups using qrata’s talent marketplaces. To sign-up please visit Qrata: https://www.qrata.co/
About the role:
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networking.
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Candidate Requirements:
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Requirements:
- Key requirements: Functional Testing, Automation, Base24 JIRA, API.
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Requirements
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5+ years of experience with developing, deploying, and debugging solutions on the AWS platform using ALL AWS services such as S3, IAM, Lambda, API Gateway, RDS, Cognito, Cloudtrail, CodePipeline, Cloud Formation, Cloudwatch and WAF (Web Application Firewall).
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Amazon Web Services (AWS) Certified Developer: Associate, is required; Amazon Web Services (AWS) DevOps Engineer: Professional, preferred.
-
5+ years of experience using one or more modern programming languages (Python, Node.js).
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Hands-on experience migrating data to the AWS cloud platform
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Experience with Scrum/Agile methodology.
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Good understanding of core AWS services, uses, and basic AWS architecture best practices (including security and scalability)
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Experience with AWS Data Storage Tools.
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Experience in Configure and implement AWS tools such as CloudWatch, CloudTrail and direct system logs for monitoring.
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Experience working with GIT, or similar tools.
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Ability to communicate and represent AWS Recommendations and Standards.
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Experience with Docker
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Experience with PostgreSQL database
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