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)