Lead digital marketing system projects for the Fast Retailing Group, from MarTech platforms such as CDP, MA and BI to marketing infrastructure for e-commerce platform rollouts.
About this role
A data analyst position on Fast Retailing's Global E-Commerce Management Strategy Team — the global headquarters of the group's e-commerce business, which identifies problems in online operations worldwide and drives their fixes. The work covers e-commerce data worth hundreds of billions of yen and feeds executive decision-making.
The role runs the full analysis cycle: defining analysis requirements, designing and aggregating, collecting, cleaning and preprocessing data, building databases, and producing visualisations and reports presented to stakeholders. The team's stack includes SQL and Python, BigQuery and Redshift, Tableau and Looker, AWS, GCP and Azure, GA4, GitHub and dbt.
Applicants need at least one year of hands-on data extraction and processing in R, Python, SQL or similar, experience with cloud infrastructure and data warehouses, and experience configuring and extracting data with BI tools. E-commerce experience is not required.
This is an AI-generated summary of the employer's original posting — details can be incomplete, out of date or simply wrong. Always confirm everything on the official posting before applying.
Similar jobs
Lead product improvement and new-product initiatives for MiiTel and related services, balancing user needs, business impact and engineering capacity while coordinating engineers and business teams.
Applied Scientist Interns build machine-learning models, analyze large-scale data, run experiments, and use GenAI/LLMs to improve search, product discovery, personalization, and customer experiences.
Strengthen group cybersecurity through policy, solution delivery, CSIRT operations, incident response and staff training while coordinating vendors and technology teams.
Designs and builds AI agents and data platforms that model management KPIs, forecast scenarios, gather external insights, and generate reports to support company decision-making.
Work alongside customer developers to embed AI-driven workflows, train users, monitor adoption and turn practical issues into product improvements.