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:
- Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) or data catalogs (Collibra, Alation, Purview); familiarity with Snowflake, Databricks, or BigQuery environments
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.
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.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Frontend
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- Solid experience in Node.js
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Good to Have:
- Cloud certifications (AWS / Azure / GCP)
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- Opportunity to work on cutting-edge tech and greenfield projects
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We are an early stage start-up, building new fintech products for small businesses. Founders are IIT-IIM alumni, with prior experience across management consulting, venture capital and fintech startups. We are driven by the vision to empower small business owners with technology and dramatically improve their access to financial services. To start with, we are building a simple, yet powerful solution to address a deep pain point for these owners: cash flow management. Over time, we will also add digital banking and 1-click financing to our suite of offerings.
We have developed an MVP which is being tested in the market. We have closed our seed funding from marquee global investors and are now actively building a world class tech team. We are a young, passionate team with a strong grip on this space and are looking to on-board enthusiastic, entrepreneurial individuals to partner with us in this exciting journey. We offer a high degree of autonomy, a collaborative fast-paced work environment and most importantly, a chance to create unparalleled impact using technology.
Reach out if you want to get in on the ground floor of something which can turbocharge SME banking in India!
Technology stack at Velocity comprises a wide variety of cutting edge technologies like, NodeJS, Ruby on Rails, Reactive Programming,, Kubernetes, AWS, NodeJS, Python, ReactJS, Redux (Saga) Redis, Lambda etc.
Key Responsibilities
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Responsible for building data and analytical engineering pipelines with standard ELT patterns, implementing data compaction pipelines, data modelling and overseeing overall data quality
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Work with the Office of the CTO as an active member of our architecture guild
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Writing pipelines to consume the data from multiple sources
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Writing a data transformation layer using DBT to transform millions of data into data warehouses.
-
Implement Data warehouse entities with common re-usable data model designs with automation and data quality capabilities
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Identify downstream implications of data loads/migration (e.g., data quality, regulatory)
What To Bring
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5+ years of software development experience, a startup experience is a plus.
-
Past experience of working with Airflow and DBT is preferred
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5+ years of experience working in any backend programming language.
-
Strong first-hand experience with data pipelines and relational databases such as Oracle, Postgres, SQL Server or MySQL
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Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development)
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Experienced with the formulation of ideas; building proof-of-concept (POC) and converting them to production-ready projects
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Experience building and deploying applications on on-premise and AWS or Google Cloud cloud-based infrastructure
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Basic understanding of Kubernetes & docker is a must.
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Experience in data processing (ETL, ELT) and/or cloud-based platforms
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Working proficiency and communication skills in verbal and written English.
location : Una , Junagadh and Gandhidham
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Full Stack Developer - Averlon