DBT Data Engineer

Job Overview We are seeking an experienced DBT Data Engineer with 8+ years of experience in data engineering, data transformation, and cloud data platforms. The ideal candidate should have strong hands-on expertise in dbt (Data Build Tool), SQL, Python, data warehousing, and cloud data platforms . The role will focus on building scalable transformation pipelines, developing reliable data models, and implementing data quality and testing frameworks. Key Responsibilities • Design, develop, and maintain scalable data transformation pipelines using dbt . • Develop complex SQL-based data models using dbt. • Build and maintain staging, intermediate, and mart layers following dbt best practices. • Implement dbt models, macros, snapshots, seeds, tests, and incremental models . • Develop reusable and optimized SQL transformations for large datasets. • Implement data quality checks and automated testing using dbt. • Build and maintain data lineage and documentation using dbt documentation . • Integrate dbt with cloud data platforms and enterprise data pipelines. • Optimize data models and SQL queries for performance and cost. • Implement incremental loading and Change Data Capture (CDC) strategies where required. • Work closely with Data Architects, Analysts, BI Developers, and Business stakeholders. • Troubleshoot data pipeline and transformation failures in development and production environments. • Implement CI/CD processes for dbt deployments using Git and DevOps tools. • Follow data governance, security, quality, and engineering best practices. • Participate in code reviews, technical design discussions, and Agile ceremonies. Must Have Skills • 8+ years of overall Data Engineering experience • Strong hands-on experience with dbt / dbt Core / dbt Cloud • Advanced SQL skills • Strong experience in data warehousing and dimensional data modeling • Experience developing dbt models, macros, snapshots, seeds, and tests • Strong understanding of incremental models and materializations • Experience with data quality and testing frameworks • Strong experience with Git and CI/CD • Hands-on experience with at least one modern cloud data warehouse: • Snowflake • Databricks • Amazon Redshift • Google BigQuery • Experience developing ETL/ELT pipelines • Strong understanding of data integration and transformation concepts • Experience with Python for data engineering/automation Nice to Have • Experience with AWS / Azure / GCP • Experience with Airflow / Dagster / Prefect • Experience with Snowflake • Experience with Databricks / Delta Lake • Experience with Amazon Redshift • Experience with Fivetran / Matillion / Informatica • Experience with Kafka or streaming data • Experience with Terraform • Experience with Docker • Experience with data governance and catalog tools • Experience working in Agile/Scrum environments Technical Skills Data Transformation: dbt, dbt Cloud, dbt Core Database/Warehouse: Snowflake, Databricks, Redshift, BigQuery Languages: SQL, Python ETL/ELT: dbt, Airflow, Fivetran, Matillion DevOps: Git, CI/CD, GitHub/GitLab/Azure DevOps Data Modeling: Star Schema, Snowflake Schema, Dimensional Modeling Cloud: AWS / Azure / GCP Data Quality: dbt Tests, Data Validation, Data Reconciliation Methodology: Agile / Scrum