Data Engineer (1-Year Renewable Contract)

Dear Applicant,

If you or someone you know is interested, please send the CV directly to [Confidential Information] (preferred, as I may overlook some CVs due to the high volume).

Please note that visa sponsorship is not available at this time.

Role Overview

We are looking for a mid-level Analytics Engineer / Data Engineer to support the development and modernization of our data and analytics platform.

The ideal candidate should have strong hands-on experience in SQL and Python, good knowledge of dimensional data modelling, and practical experience with dbt or equivalent transformation frameworks and workflow orchestration tools. The candidate should also understand modern software engineering practices such as Git, testing, and CI/CD.

Required Skills

• 3 to 6 years of relevant experience in Data Engineering, Analytics Engineering, Data Warehousing, or related areas.
• Strong hands-on experience with SQL.
• Good working knowledge of Python for data processing and automation.
• Experience with dimensional data modelling, including Star schemas, Fact tables, Dimension tables, Data marts
• Hands-on experience with dbt or an equivalent data transformation framework.
• Experience with at least one workflow orchestration tool, such as Airflow or equivalent.
• Understanding of semantic layers, common business metrics, and reusable business logic.
• Knowledge of software development best practices including Git/version control, Code reviews, Unit/data testing, CI/CD
• Good understanding of ETL/ELT and data warehouse concepts.
• Ability to troubleshoot data and pipeline issues independently.
• Good communication and collaboration skills.

Good-to-Have Skills

• Experience working with Google Cloud Platform (GCP).
• Exposure to BigQuery, Cloud Composer, Cloud Storage, and other GCP data services.
• Ability to understand existing .NET business logic and assist in converting or redesigning the processes using appropriate cloud-native technologies.
• Familiarity with BI and reporting tools and how analytical datasets are consumed by business users.