Snowflake Data Engineer w/ Airflow & DBT :: 10+ Years experienced is a must
Summary
Build and optimize cloud data pipelines in Snowflake, orchestrate workflows with Airflow, and transform data using dbt to support enterprise analytics.
Role: Snowflake Data Engineer with Apache Airflow & DBT experience
Experience: 10+ Years
Location: Dubai (Hybrid/Onsite as per business requirement)
About the Role:
We are seeking a highly skilled Snowflake Data Engineer with 10+ years of experience in designing, developing, and optimizing modern cloud-based data platforms. The ideal candidate should have strong hands‑on expertise in Snowflake, advanced SQL, and cloud data engineering practices, with mandatory experience in Apache Airflow and dbt (Data Build Tool).
The role involves building scalable data pipelines, implementing ELT frameworks, optimizing data models, and supporting enterprise analytics initiatives.
Key Responsibilities:
Design, develop, and maintain scalable data pipelines using Snowflake.
Build and optimize ELT workflows using dbt.
Develop and orchestrate data pipelines using Apache Airflow.
Design and implement efficient data models to support analytical and business reporting requirements.
Perform data ingestion from multiple structured and semi‑structured data sources.
Optimize Snowflake performance through query tuning, clustering, partitioning, and warehouse optimization.
Develop reusable, scalable, and maintainable SQL transformations.
Implement data quality checks, validation, and monitoring processes.
Collaborate with Data Architects, Business Analysts, BI Developers, and cross‑functional teams to deliver robust data solutions.
Troubleshoot production issues and ensure high availability of data pipelines.
Follow best practices for version control, CI/CD, testing, and documentation.
Required Skills:
10+ years of experience in Data Engineering.
Strong hands‑on experience with Snowflake.
Advanced SQL programming and query optimization.
Mandatory experience with Apache Airflow.
Mandatory experience with dbt (Data Build Tool).
Strong understanding of ETL/ELT concepts and modern data engineering practices.
Experience building and maintaining enterprise‑scale data pipelines.
Proficiency in Python for data engineering and automation.
Experience working with Git and version control.
Good understanding of data modeling techniques (Star Schema, Snowflake Schema, Dimensional Modeling).
Experience working with structured and semi‑structured data formats such as JSON, Parquet, and Avro.
Strong analytical, debugging, and problem‑solving skills.
Preferred Skills:
Experience with Azure, AWS, or Google Cloud Platform.
Exposure to data lake and lakehouse architectures.
Experience with Azure Data Factory, Fivetran, Informatica, or similar integration tools.
Knowledge of CI/CD pipelines and DevOps practices.
Familiarity with Power BI, Tableau, or other BI platforms.
Understanding of data governance, security, and access management within Snowflake.
Snowflake certification is an added advantage.
- Snowflake
- dbt
- SQL
- Python
- ETL/ELT
- Data Modeling
- Performance Optimization
- Git
- CI/CD
- Problem Solving
Educational Qualification:
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
Good to Have:
Experience in Agile/Scrum environments.
Strong communication and stakeholder management skills.
Experience working on enterprise‑scale data modernization or cloud migration projects.