Data Engineer Senior Associate - Group Service

Founded in 2020, Seven Retail is a House of Brands focused on making quality lifestyle services more accessible. With over 200 centers and growing, we operate across F&B, Education, Healthcare, and Lifestyle Services.

We are on a mission to make increasingly higher quality, premium lifestyle services accessible to everyone, helping people get more out of their paycheck so everybody can experience a higher standard of living.

Ready to take the next step in your career? Join us as a **Data Engineer Senior Associate - Group Service and discover what you can achieve at Seven Retail. Read on to learn more!

Your Day-to-Day

• Architect, deploy, and manage scalable data models and storage structures using Google Cloud Platform (GCP), particularly BigQuery.
• Design, develop, and optimize resilient ETL/ELT pipelines to integrate data from CRM systems, LMS, Google Sheets, and advertising platforms such as TikTok Ads, Meta Ads, and Google Ads.
• Build automated workflows to enable reliable real-time or near-real-time data integration across platforms.
• Establish and maintain data standards covering quality, security, privacy, and compliance throughout the data lifecycle.
• Optimize BigQuery query performance, data partitioning, and storage costs to improve infrastructure efficiency.
• Collaborate with Analytics teams to build production-ready data marts and support data visualization best practices using tools such as Apache Superset.
• Drive engineering best practices through CI/CD, version control, automated testing, and technical documentation.

Who We’re Looking For**

• Minimum 3 years of experience in Data Engineering, Cloud Architecture, or related data platform roles.
• Strong hands-on expertise in Google Cloud Platform (GCP), particularly BigQuery.
• Expert-level proficiency in SQL and Python, with experience using orchestration tools such as Apache Airflow and transformation frameworks such as Dataform or dbt.
• Advanced knowledge of BigQuery schema design, data warehousing methodologies (Kimball/Inmon), and large-scale data processing.
• Experience integrating REST APIs and developing custom data connectors.
• Strong understanding of data testing frameworks, CI/CD pipelines, version control, and containerization tools such as Docker.
• Strong ownership and initiative, with the ability to independently drive data engineering projects from architecture to production and guide technical decisions.
• Adaptable and proactive, with the ability to navigate evolving business needs and continuously improve data infrastructure.