Data Engineer

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Short Description for Internal Candidates

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.

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Description for Internal Candidates

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.

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Responsibilities for Internal Candidates

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: 

o         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: 

o         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.

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Qualifications for Internal Candidates

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)