DBT Developer with AWS

Role : DBT Developer with AWS

Location : Pleasanton ,CA

Description

• Design, develop, and maintain scalable dbt models and ELT pipelines for enterprise data platforms.
• Develop staging, intermediate, fact, and dimension models using dbt and advanced SQL.
• Build complex SQL transformations using CTEs, joins, window functions, aggregations, and subqueries.
• Develop and optimize incremental dbt models for large-volume datasets.
• Create reusable dbt macros using Jinja to standardize transformation logic.
• Develop custom data quality tests and implement validation rules for critical datasets.
• Configure and maintain dbt sources, snapshots, seeds, exposures, documentation, and lineage.
• Implement source freshness monitoring and data quality checks.
• Build and maintain AWS-based data pipelines using services such as Amazon S3, AWS Glue, Amazon Redshift, Lambda, Step Functions, and CloudWatch.
• Develop data lake solutions using Amazon S3 for raw, curated, and processed datasets.
• Create and maintain AWS Glue ETL jobs, Crawlers, and Data Catalog configurations.
• Develop optimized analytical models in Amazon Redshift.
• Optimize SQL queries and Redshift workloads to improve performance and reduce compute costs.
• Orchestrate dbt and AWS data pipelines using Apache Airflow, Amazon MWAA, or other workflow orchestration tools.
• Implement automated deployment pipelines for dbt using AWS CodePipeline, CodeBuild, GitHub Actions, Jenkins, or similar CI/CD tools.
• Integrate dbt development with Git-based source control, branching strategies, pull requests, and code reviews.
• Automate dbt execution including dbt build, dbt run, dbt test, and documentation generation.
• Implement secure AWS access using IAM roles, policies, KMS, and AWS Secrets Manager.
• Monitor production data pipelines using Amazon CloudWatch and troubleshoot failures.
• Perform root-cause analysis for dbt, SQL, AWS Glue, Redshift, and data quality issues.
• Work with data engineers and business stakeholders to convert business requirements into scalable data solutions.
• Maintain technical documentation for data models, pipelines, data lineage, and operational procedures.
• Participate in Agile/Scrum ceremonies, sprint planning, backlog refinement, code reviews, and production releases.