About this role
We are looking for a skilled Data Engineer with strong DBT experience to design, develop, and optimize scalable data transformation pipelines on modern cloud data platforms. The ideal candidate should have hands-on expertise in DBT (Data Build Tool), SQL, cloud data warehouses, and ELT processes.
The role will involve building analytics-ready datasets, implementing data quality frameworks, and collaborating with data architects, analysts, and business stakeholders to deliver reliable and scalable data products.
Key Responsibilities
Data Engineering & ELT Development
• Design and develop ELT pipelines using DBT. • Build reusable, scalable, and maintainable data transformation models. • Develop staging, intermediate, and mart layers following DBT best practices. • Implement modular SQL transformations and macros. • Create and maintain source-to-target mappings.
Data Modeling
• Design dimensional models, fact tables, and star schemas. • Build business-friendly semantic layers for reporting and analytics. • Support enterprise data warehouse initiatives.
Data Quality & Testing
• Implement DBT tests for: • Uniqueness • Referential integrity • Null validation • Custom business rules
• Monitor and improve overall data quality. • Perform root cause analysis for data issues.
Cloud Data Platform Development
• Work with cloud platforms such as: • Snowflake • Databricks • BigQuery • Azure Synapse • Redshift
• Optimize query performance and manage compute costs.
CI/CD & DevOps
• Integrate DBT projects with Git and CI/CD pipelines. • Automate deployments across Development, QA, and Production environments. • Maintain documentation and lineage using DBT documentation features.
Collaboration
• Work closely with Data Architects, Analysts, and Business Teams. • Participate in Agile ceremonies and sprint planning. • Translate business requirements into scalable data solutions.
Required Skills
Core Technical Skills
• DBT (Data Build Tool) • Advanced SQL • Data Warehousing Concepts • Data Modeling • ETL / ELT Development
Cloud Platforms
• Snowflake • Databricks • Google BigQuery • Azure Synapse Analytics • AWS Redshift
Programming
• Python • SQL • Shell Scripting (Preferred)
Data Engineering Tools
• Airflow • Azure Data Factory • Databricks Workflows • GitHub / GitLab
Data Quality & Governance
• Data Lineage • Data Catalog • Data Validation Frameworks • Metadata Management
Desired Experience
• Experience building DBT models on Snowflake or BigQuery. • Experience implementing data validation checks and automated testing through DBT. • Experience creating analytics-ready datasets and semantic models. • Exposure to Medallion Architecture, Lakehouse, and Modern Data Platforms.
Qualifications
• Bachelor's degree in Computer Science, Engineering, Information Technology, or related field. • 4–8 years of Data Engineering experience. • Minimum 2+ years of hands-on DBT development experience.
Preferred Certifications
• SnowPro Certification • Databricks Data Engineer Associate/Professional • Google Professional Data Engineer • Microsoft Azure Data Engineer Associate
Nice-to-Have Skills
• DBT Cloud • Jinja Macros • Terraform • Kafka • Spark/PySpark • Data Vault 2.0
AI-assisted development tools (GitHub Copilot, Microsoft Copilot)