Lead Assistant Manager

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)