Job Summary
Highly skilled Data Engineer with strong expertise in Snowflake and dbt should possess extensive hands-on experience in designing, building, optimizing, and maintaining modern cloud-based data platforms. The candidate must have a strong foundation in Data Warehousing, ETL/ELT processes, Data Modeling, SQL, and RDBMS technologies along with the ability to develop scalable and high-performing data solutions.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Snowflake and dbt.
- Build and optimize data warehouse solutions to support analytics and reporting requirements.
- Develop ELT/ETL frameworks and data transformation processes using industry best practices.
- Design and implement dimensional and normalized data models.
- Write Complex SQL queries when required.
- Create reusable dbt models, macros, tests, snapshots, and documentation.
- Optimize Snowflake performance, storage, and compute costs.
- Develop and maintain data ingestion frameworks from various source systems.
- Implement data quality checks, monitoring, and governance controls.
- Collaborate with business analysts, architects, and stakeholders to translate business requirements into technical solutions.
- Troubleshoot and resolve production issues related to data pipelines and warehouse performance.
- Ensure adherence to security, compliance, and data management standards.
Skill Requirements
Snowflake
- Strong hands-on experience in Snowflake architecture and administration.
- Expertise in:
- Virtual Warehouses
- Snowflake Storage & Compute Optimization
- Complex Query writing and Performance Tuning
- Clustering & Partitioning Strategies
- Snowpipe
- Streams & Tasks
- Time Travel & Fail-safe
- Data Sharing
- Role-Based Access Control (RBAC)
- Experience with Snowflake migration projects and performance optimization.
dbt
- Extensive hands-on experience in:
- dbt Core and/or dbt Cloud
- dbt Models
- Macros
- Seeds
- Snapshots
- Incremental Models
- CI/CD Integration
- Data Lineage and Governance
Data Warehousing
- Strong understanding of:
- Dimensional Modeling
- Star and Snowflake Schemas
- Data Lake and Data Warehouse Architectures
- SCD Type 1 & Type 2 Implementations
ETL / ELT
- Extensive experience in designing and implementing ETL/ELT solutions.
- Expertise in handling complex data transformations and large-volume data processing.
Databases
Strong knowledge of multiple RDBMS platforms including:
- Oracle/SQL Server/PostgreSQL etc..
Other Requirements
Good to Have Skills
- Cloud platforms: AWS, Azure, or GCP.
- Data integration tools such as Informatica, Matillion, Fivetran, Talend, or Azure Data Factory.
- CI/CD tools such as GitHub, GitLab, Azure DevOps, Jenkins.
- Exposure to data governance and data quality frameworks.