• Maintain our data products with timely and quality data.
• Collaborate with internal and external stakeholders to collect business requirements and define successful analytics outcome.
• Design, develop and extend dbt code to extend the Enterprise Dimensional Model.
• Maintain data catalog, provide a scalable resource to support self-service and a single source of truth analytic.
• Advocate data quality and data governance to ensure all data provided are in the highest standard.
• Implements the data ops philosophy in everything you do.
• Research new data and analytic engineering methodologies with menial guidance and support from other team members.
• Able to take end-to-end responsibility on projects of increasing complexity.
• Serve as data model subject matter expert and data model spokesperson, demonstrated by the ability to address questions quickly and accurately.
• Mentors junior engineers via pairing, design review, and code review.
• Review and improve the data system as a whole, inclusive data model designs, process flows, and use cases.
  

Requirements

• At least 2+ years of experience in data modelling or data analytic or data engineering.
• Strong Competency in SQL, Python, and cloud infrastructure (Preferably GCP), knowledge in DBT.
• Experience in building solid ETL or ELT framework and Multiple data integration projects.
• Expert in data modelling best practice (Dimensional modelling) for large scale data warehousing or OLAP system.
• Able to document plans and results in either issue and releases.
• Strong understanding of data quality and data governance.
• Able to use code version control systems, follow the naming convention and standard code style.
• Expert in multiple data visualization tools.