Data Engineer – Build Scalable Pipelines with Snowflake & dbt

About the role

We are looking for a Data Engineer with 4‑6 years of experience to design, build, and maintain reliable data pipelines that feed analytics across the business. You will collaborate with cross‑functional teams and work on a modern stack that includes Snowflake, Python, SQL, and dbt.

Key responsibilities

• Build end‑to‑end data pipelines into Snowflake from APIs, databases, S3, SFTP and file‑based sources.
• Develop and optimise dbt models for Orders, Inventory, Products, Customers, Finance and Marketing.
• Manage dbt Cloud jobs, semantic models, testing and deployment processes.
• Design Snowflake objects such as tasks, stages, views and data sharing configurations.
• Create Python‑based ETL/ELT workflows and write high‑performance SQL for reporting.
• Monitor pipeline health, implement data‑quality checks and resolve production incidents within SLA.
• Support platform modernisation, legacy migrations, CI/CD pipelines and cloud data infrastructure.
• Partner with Analytics, Marketing, Operations, DevOps, Privacy and external stakeholders.

Required profile

• 4‑6 years of hands‑on Data Engineering experience.
• Strong expertise with Snowflake, SQL, Python and dbt.
• Proven ability to build scalable ETL/ELT pipelines and optimise data warehouses.
• Experience with version control (Git) and CI/CD processes.
• Excellent analytical, troubleshooting and communication skills.

Required skills

• Snowflake
• SQL
• Python
• dbt
• Git
• CI/CD
• AWS services (S3, Lambda, Glue)
• Airflow or similar orchestration tools
• Fivetran or comparable ELT tools
• BI platforms (Sigma, Tableau, Power BI, Looker)
• Docker
• Kubernetes