Senior Data Scientist & AI Engineer advancing RLD Foundation’s data strategy in a collaborative environment. Building data infrastructure and conducting analytics to support social impact initiatives.
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
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Not specified
Degree requirement
Tech skills
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