
Key Data Engineering Role
1 week ago
We are seeking an experienced and skilled Data Engineer to join our growing Data Engineering team. The ideal candidate will have a strong background in building scalable, high-performance data transformation pipelines using Snowflake and dbt.
">Job Responsibilities:
- Design and implement efficient ELT pipelines using dbt on Snowflake, adhering to industry-accepted best practices.
- Build ingestion pipelines from various sources, including relational databases, APIs, cloud storage, and flat files into Snowflake.
- Implement data modelling and transformation logic to support layered architecture (e.g., staging, intermediate, and mart layers or medallion architecture) for reliable and reusable data assets.
- Utilize Airflow, dbt Cloud, or Azure Data Factory to schedule and monitor data workflows.
- Apply dbt best practices: modular SQL development, testing, documentation, and version control.
- Perform performance optimizations in dbt/Snowflake through clustering, query profiling, materialization, partitioning, and efficient SQL design.
- Apply CI/CD and Git-based workflows for version-controlled deployments.
- Collaborate with multiple stakeholders, including data analysts, data scientists, and data architects, to understand requirements and deliver clean, validated datasets.
- Participate in Agile ceremonies, including sprint planning, stand-ups, and retrospectives.
Requirements:
- 3 to 5 years of experience in data engineering roles, with 2+ years of hands-on experience in Snowflake and dbt.
- Experience building and deploying dbt models in a production environment.
- Expert-level SQL and strong understanding of ELT principles. Strong understanding of ELT patterns and data modelling (Kimball/Dimensional preferred).
- Familiarity with data quality and validation techniques: dbt tests, dbt docs, etc.
- Experience with Git, CI/CD, and deployment workflows in a team setting.
- Familiarity with orchestrating workflows using tools like dbt Cloud, Airflow, or Azure Data Factory.
Preferred Qualifications:
- Cloud Data Platform Expertise: Strong proficiency with Snowflake: warehouse sizing, query profiling, data loading, and performance optimization.
- Experience working with cloud storage (Azure Data Lake, AWS S3, or GCS) for ingestion and external stages.
- Knowledge of modern data architecture concepts including layered architecture (e.g., Familiarity with data quality, unit testing (dbt tests), and documentation (dbt docs).
- Understanding of access control within Snowflake (RBAC), role hierarchies, and secure data handling.
- Familiar with data privacy policies (GDPR basics), encryption at rest/in transit.
- DevOps and Automation: Version control using Git, experience with CI/CD practices in a data context.
- Monitoring and logging of pipeline executions, alerting on failures.
What We Offer:
- A collaborative work culture that values innovation and curiosity.
- Access to cutting-edge technologies and a focus on professional development.
- Competitive compensation and benefits package.
- The opportunity to work on diverse and challenging projects in a consulting environment.
As a member of our team, you will have the chance to work on impactful data solutions, collaborate with experts, and continuously develop your skills in a dynamic environment.
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