DBT Cloud Data Engineer

Your Role

• Has 8–12 years of IT experience with minimum 6 years of experience in data warehouse, data lakes, ETL/ELT, and data pipelines on cloud. Has strong data pipeline implementation experience with at least one cloud provider – AWS, Azure, or GCP.
• Experience with cloud storage, cloud database, cloud data warehousing and Data Lake solutions like Snowflake, BigQuery, AWS Redshift, ADLS, S3.
• Advanced expertise in dbt (data build tool), including designing enterprise-grade dbt projects, reusable macros, environment management (dev/test/prod), and performance tuning of dbt models.
• Strong experience in designing scalable ELT architectures using dbt as the transformation layer and implementing layered data models (staging, intermediate, marts). Ability to troubleshoot and fine-tune data workflows and dbt models to handle high data volume and velocity.
• Experience in designing reusable data transformation frameworks and standardized data models using dbt. Hands-on experience implementing monitoring, logging, alerting, and observability for pipelines and dbt jobs.

Your Profile

• Must have completed at least one full end-to-end implementation cycle using dbt in a production environment. Good knowledge of cloud compute services, load balancing, networking, identity management (IAM), authentication, and authorization. Proficient in implementing serverless components (AWS Lambda, Azure Functions, Step Functions, Cloud Run) for orchestration and automation.
• Experience in using cloud data integration services such as Azure Databricks, Azure Data Factory, Azure Synapse Analytics, AWS Glue, AWS EMR, Dataflow, Dataproc. Strong understanding of integrating dbt with orchestration tools such as Airflow, Azure Data Factory, or dbt Cloud.
• Good knowledge of infra capacity sizing, cost optimization, and performance tuning of cloud solutions. Able to contribute to architectural decisions using cloud services and solution methodologies. Strong proficiency in Python for developing reusable ETL frameworks, APIs, and automation scripts.
• Good working knowledge and hands-on experience in PySpark, cloud DevOps practices such as Infrastructure as Code, CI/CD, automated deployments, including dbt CI/CD and testing strategies.Strong understanding of networking, security, design principles, and cloud best practices.
• Ability to lead architectural and technical discussions with clients and drive adoption of best practices including dbt-based transformations. Excellent communication and presentation skills.

What you will love about working here

• We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. 
• At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. 
• Equip yourself with valuable certifications in the latest technologies such as Generative AI.