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)