- Job Role: Application Development-Cloud Development
- Experience (In Years): 3-6
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.
Responsibilities
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.
Qualifications
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)
