

Qiang MENG
Technical Expertise: With 15 years of laser-focused experience in data engineering, I bring a proven track record of delivering scalable, impactful solutions that drive business growth and operational efficiency.
As Head of Data Engineering at N Br*wn's Group, I led a multidisciplinary team of 20+ individual contributors across Data Architect, Data Engineering, Machine Learning Engineering, Platform DevOps, and Front-end Analytics Engineering. On my first day, I stabilized a collapsing team and, within two months, redirected two £20M projects back on track. Partnering with Datatonic, I delivered a modern GCP analytics platform foundational for this 160-year-old UK retailer—all within three months.
At L*vis, as Global Data Engineering Manager, I built the FEOPS (Feature Engineering for AI Operations) team from scratch in 2020. By 2024, the team of 15+ engineers from 13 countries was named one of the Global Top 10 Data and Analytics Teams by DataIQ. Under my leadership, we developed a comprehensive data strategy for use cases such as Product Assortment, Stock Allocation, Pricing, and Promotions, driving $24M in annual business profits. A standout achievement was establishing L*vis first Feature Store within just three months, setting a new benchmark for innovation.
Leadership and Stakeholder Engagement: I excel in team building and stakeholder engagement, creating high-performing, collaborative teams aligned with organizational goals. My approach emphasizes mentorship, the implementation of engineering best practices, and fostering a culture of innovation. I have successfully managed cross-functional global teams, established clear processes and documentation, and ensured alignment with both technical and business objectives.
Passion for Retail and Innovation: Driven by an unwavering passion for retail, I channel my expertise to innovate and solve complex business challenges. My enthusiasm for the industry keeps me motivated to push boundaries, embrace the latest advancements in Data and AI, and deliver results at pace. Whether it is enabling AI-driven garment design or transforming data ecosystems, my commitment is to make impactful contributions that drive business success.
As a data leader with deep technical expertise, a track record of building high-performing teams, and a passion for retail, I am eager to take on a Head of Data or Head of Data Engineering role. I aim to leverage my skills and drive to lead transformative data initiatives in the retail and fashion industry.
Work Data, Feature, and Software Engineering: Building better tech together.
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IBM Mainframe (IBM Z) GCP Migration - N Br*wn, 2024
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GCP Analytics Platform Foundation - N Br*wn, 2025
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Enterprise Data Science Feature Store (FS) - L*VIS, 2023
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LakeHouse Data Catalog - L*VIS, 2021
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EU Data Lake - L*VIS, 2021
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ARC (Analytics Reporting Center) - L*VIS, 2024
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Centralized Data Lake - H&M Gr*up, 2020
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Petabyte-scale Cloud Migration (AWS to GCP) - L*VIS, 2022
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Miniboard (Reporting Dashboard) - SoftB*nk Robotics, 2018
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Data ETL Framework - SoftB*nk Robotics, 2017
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Sales & Performance Dashboard - Kps*le, 2014
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AWS Serverless ETL Framework - SoftB*nk Robotics, 2018
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Real-Time Stats Controller - Kps*le, 2016
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HDFS-K ETL Framework - Kps*le, 2015
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Airline Scheduling Optimization System - Amad*us, 2012
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Back Office Management System - Kps*le, 2013
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Bionewmetrics (Computational Biology Wikipedia) - ENS (École Normale Supérieure), 2011
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Next?
Way of Working Unlocking Efficiency through Industrialized Data Engineering.
Conferences Unlock the power of data and AI with my expert insights.
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Scale and Optimize Data Engineering Pipelines with Best Practices: Modularity and Automated Testing - Data + AI Summit 2020
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5 Recipes to Scale your Airflow Data Pipelines - Data Innovation Summit 2021
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Mastering Airflow Data Engineering: Five Fashionable Recipes - PyCon 2021
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Next?
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Fashion Retail, fashion, and art merge in a beautiful fusion of creativity, expression, and commerce.
Contact Eagerly await the chance to connect with you
Qiang MENG
qmeng1987@gmail.com
+44 7521 084 734
(11h-13h, after 17h, BST)
London, UK