Data Scientist for Product Sustainability at Roche managing environmental data for sustainability reporting. Bridging Global Sustainability Experts and IT systems to ensure actionable insights for product emissions and compliance.
About the role
- Lead Data Engineer revamping company’s data infrastructure at OnTheList, a premium flash sales platform in Asia and the Middle-East. Collaborate with stakeholders and drive technical data strategy to support business growth.
Responsibilities
- Lead the end-to-end revamp of the company’s data infrastructure, defining and executing a scalable architecture that supports analytics, reporting, and business growth.
- Partner with group level business stakeholders to translate data needs into effective reporting and analytical solutions, supporting day-to-day requests and strategic decision-making.
- Own and drive the overall data strategy, ensuring alignment between business objectives and technical data architecture.
- Provide technical leadership and mentorship to junior data engineers, fostering best practices and continuous improvement across the data team.
- Design, implement, and maintain high-performance data pipelines and warehouse solutions that enable reliable and timely access to business-critical information.
- Integrate and manage data from diverse platforms including ERP, CRM, and e-commerce systems (e.g., Shopify) to support daily sales reporting, inventory analysis, and performance tracking.
- Build, deploy, and manage cloud-based data infrastructure on AWS, leveraging services such as Redshift, EMR, EC2 and RDS, and related technologies for reliability and scalability.
- Ensure data governance, reliability, security, and protect sensitive data from unauthorized access or breaches.
- Proactively monitor and optimize system performance, resolving bottlenecks and ensuring high availability, scalability, and efficiency across data platforms.
- Develop and maintain data models, dashboards, and BI tools that deliver actionable insights to functional teams.
Requirements
- Bachelor’s degree in Computer Science, Data Science, or a related quantitative field.
- 6+ years of professional experience in data engineering, with hands-on expertise in building a large-scale data infrastructure.
- Hands-on experience with Data Lake and Data Warehouse architecture design, maintain and scaling.
- Proficiency with Databricks, Snowflake, Amazon Redshift, and Google BigQuery.
- Experience with both batch and streaming data processing.
- Strong understanding of retail and e-commerce data flows (Shopify, ERP, POS) and how to translate them into automated sales and performance reporting.
- Strong programming skills in SQL and Python; knowledge of Scala or R is a plus.
- Strong analytical skills and experience working with structured and unstructured data.
- Proficiency in working with relational databases (e.g., PostgreSQL) as well as NoSQL databases (e.g., MongoDB).
- Experience with Spark, Hive, Hadoop, or EMR is a plus.
- Solid understanding of data modeling, data access patterns, and storage design.
- Proficiency in BI platforms including AWS QuickSight, Power BI, Looker Studio, and Tableau.
- Hands-on experience building and scaling ETL/ELT data pipelines with modern tools (e.g., Airbyte) and optimizing data architectures for performance and reliability.
- Exposure to AI-driven data innovation or advanced analytics to uncover insights and support data-informed business decisions is a strong advantage.
- Strong problem-solving skills with an ability to analyze complex datasets efficiently.
- Excellent communication skills to effectively collaborate with cross-functional teams.
- Fluent in English (spoken and written), proficiency in Cantonese and Mandarin is advantageous.
Benefits
- Health insurance
- Flexible work arrangements
- Professional development
Job title
Job type
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Not specified
Degree requirement
Tech skills
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