Location: Pan India First preference to Pune

Experience: 11-15 Years

Notice Period: Immediate to max 30 days.

Must Have: Data Build Tool (DBT) experience of minimum 3 Years; Overall 9+ Years into Data Engineering and Analytics; 3+ years of Databricks development experience; AWS cloud-based data platforms; AWS cloud-based data platforms

DBT Architect responsible for building and managing transformation pipelines in a Databricks Lakehouse environment hosted on AWS, working alongside Data Engineers, Architects, and Business teams.

Required Technical Skills

Core Technologies

- Strong expertise in DBT Core and/or DBT Cloud.
- Advanced SQL development experience.
- Hands-on experience with Databricks Lakehouse Platform.
- Experience with Delta Lake, Unity Catalog, and Databricks Workflows.
- Strong understanding of data warehousing and dimensional modeling concepts.

Data Engineering

- Knowledge of ETL/ELT design patterns.
- Experience working with large-scale datasets.
- Understanding of batch and near real-time processing concepts.
- Performance tuning and optimization of SQL transformations.

DevOps & Automation

- GitHub, GitLab, or Azure DevOps
- CI/CD pipeline implementation
- Automated testing frameworks
- Infrastructure-as-Code exposure preferred

Job Summary

An experienced DBT Architect to design, develop, and optimize data transformation pipelines within a modern cloud-based data platform built on Databricks Lakehouse hosted on AWS. The ideal candidate will have solid expertise in DBT (Data Build Tool), SQL development, data modeling, and cloud-native data engineering practices.

The role involves transforming raw and curated data into business-ready datasets, implementing best practices for data quality, testing, documentation,



and CI/CD automation while collaborating closely with data architects, data engineers, analysts, and business stakeholders.

Key Responsibilities

Data Transformation & Modeling

- Design, develop, and maintain scalable data transformation pipelines using DBT in Databricks.
- Develop and manage DBT models including staging, intermediate, and mart layers.
- Implement dimensional data models (Star Schema, Snowflake Schema, Data Vault) based on business requirements.
- Translate business requirements into reusable, maintainable, and performant data models.

Databricks Development

- Build and optimize transformation logic leveraging Databricks SQL and Delta Lake capabilities.
- Develop efficient data processing workflows within Databricks Lakehouse architecture.
- Optimize data transformations for performance, scalability, and cost efficiency.
- Implement partitioning, clustering, and Delta Lake optimization techniques.

Data Quality & Governance

- Implement data quality checks, validations, and testing using DBT tests.
- Develop custom DBT macros and reusable components.
- Create data lineage and maintain metadata documentation.
- Ensure adherence to data governance and security standards.

CI/CD & DevOps

- Implement and manage CI/CD pipelines for DBT deployments.
- Automate testing, deployment, and monitoring processes.
- Integrate DBT with Git-based source control systems.
- Support code reviews and enforce development standards.

Collaboration & Stakeholder Engagement

- Collaborate with Data Architects and Data Engineers to design end-to-end data solutions.
- Work with business users and analytics teams to understand reporting and analytical requirements.
- Mentor junior developers and promote best practices across the team.
- Participate in agile ceremonies including sprint planning, retrospectives, and code reviews.

📌 DBT Architect (India)
🏢 Wipro
📍 India