dbt Architect

We are looking for an experienced DBT Architect to design, develop, and optimize modern data transformation solutions in a Databricks Lakehouse environment hosted on AWS. The ideal candidate will have strong hands-on expertise in DBT, SQL, Databricks, AWS, data modeling, and cloud data engineering. You will work closely with data engineers, data architects, analytics teams, and business stakeholders to build scalable, reliable, and high-performance data platforms.

The core responsibilities for the job include the following:

DBT and Data Transformation:

• Design, develop, and maintain scalable data transformation pipelines using DBT and Databricks
• Develop and manage DBT models across staging, intermediate, and mart layers
• Build reusable DBT models, macros, tests, and transformation components.
• Translate business requirements into scalable and maintainable data models.
• Optimize SQL transformations for performance and cost efficiency.

Databricks and Data Engineering:

• Develop transformation solutions using Databricks SQL, Delta Lake, and Lakehouse architecture
• Build and optimize Databricks workflows for large-scale data processing.
• Apply partitioning, clustering, and Delta Lake optimization techniques.
• Work with ETL/ELT design patterns for batch and near-real-time data processing.
• Handle large-scale datasets and complex transformation requirements.

Data Modeling, Quality, and Governance:

• Design dimensional models using Star Schema, Snowflake Schema, and/or Data Vault
• Implement data quality checks and automated testing using DBT tests
• Maintain DBT documentation, metadata, and data lineage.
• Develop data validation frameworks and reusable quality checks.
• Follow data governance, security, and development standards.

DevOps and CI/CD:

• Implement and manage CI/CD pipelines for DBT deployments
• Integrate DBT projects with GitHub, GitLab, or Azure DevOps
• Automate testing, deployment, and monitoring processes.
• Participate in code reviews and establish development best practices.
• Exposure to Infrastructure as Code (IaC) is preferred.

Architecture and Collaboration:

• Collaborate with data architects and data engineers on end-to-end cloud data solutions.
• Work with analytics and business teams to understand reporting and analytical requirements.
• Provide technical guidance and mentor junior team members.
• Participate in Agile ceremonies, sprint planning, retrospectives, and technical discussions.

Requirements:

• 4+ years of hands-on experience with DBT (Data Build Tool).
• 9+ years of overall experience in data engineering/data analytics.
• 3+ years of hands-on Databricks development experience.
• Strong experience working with AWS cloud-based data platforms.
• Strong expertise in DBT Core and/or DBT Cloud.
• Advanced SQL development.
• Hands-on experience with Databricks Lakehouse.
• Strong knowledge of Delta Lake, Unity Catalog, and Databricks Workflows.
• Strong understanding of data warehousing and dimensional modeling.

Required Technical Skills:

• Must Have: DBT Core / DBT Cloud, Advanced SQL, Databricks, Databricks Lakehouse, Delta Lake, Unity Catalog, Databricks Workflows, AWS, Data Warehousing, Dimensional Data Modeling, ETL / ELT, Git, CI/CD, DBT Testing, and Documentation.
• Good to Have: Infrastructure as Code, Terraform, near-real-time data processing, Data Vault, advanced Databricks optimization, cloud-native data engineering architecture.

Ideal Candidate Profile:

• 12-16 years of overall experience with at least 9+ years in data engineering/analytics, including 4+ years of strong hands-on DBT experience and 3+ years of Databricks development The candidate should be comfortable owning DBT architecture and development while working within an AWS + Databricks Lakehouse ecosystem.