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