Description

We are looking for a skilled Data Engineer with strong DBT experience to design, develop, and optimize scalable data transformation pipelines on contemporary 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)

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