Data Engineer Senior Associate - Group Service

Seven Retail | Retail

1h 9m ago

On-site

Full Time

Indonesia

Our Company

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.

Required Skills

gcpbigquerysqlpythonairflowdbtdocker

Required Languages

🇬🇧 English

Our Company

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.