Paid Media, Search & Influencer & Consumer Analytics

• Effectiveness & Audience Tracking: Build tracking frameworks to evaluate paid media performance across Meta, TikTok, and Google Ads. Engineer data models to track the efficiency of advanced targeting strategies, including Lookalike Audience performance and Audience Suppression lists across platforms.
• Search & Influencer Insights: Integrate search engine insights and keyword trends into the data ecosystem. Build custom analytics frameworks to evaluate the ROI, engagement, and conversion impact of influencer marketing campaigns.
• Consumer Journey Analysis: Supporting the business to leverage 1st party & 3rd party consumer data to build analytics framework to evaluate the consumer journey such as basket analysis, campaign evaluation, product pathway analysis etc.

Market Intelligence & Consumer Survey ETL

• Survey Data Engineering: Own the ETL preparation and normalization of primary market research, consumer trackers, and brand health survey data (e.g., Qualtrics, Toluna, or customized agency reports).
• Insights Consolidation: Harmonize qualitative survey data and market intelligence with quantitative transactional data (POS, CRM, and eCommerce sales) to create a 360-degree view of consumer behavior.

Data Pipeline Engineering, APIs & Visualization

• API Integration: Connect, maintain, and optimize data pipelines pulling from digital media APIs, CRM systems, and Google Analytics.
• Dashboard Architecture: Design, build, and maintain enterprise-grade interactive dashboards using Power BI and Tableau that translate media, survey, and sales metrics into actionable business strategies.
• User Support: Act as the primary technical point of contact to resolve basic user queries, troubleshoot dashboard issues, and manage ad-hoc deep-dive data requests.

 AI Automation & Enablement

• Workflow Automation: Utilize advanced AI scripting, tools, or GenAI workflows to automate messy media data cleaning, categorize ad creatives, and streamline routine reporting. Working with the IT team to ensure data process governance.
• Training Material & Use Cases: Author technical data dictionaries and user manuals. Formulate real-world retail use cases and support on training sessions to enable marketing and business teams to self-serve on dashboards.

Experience & Industry Background

• Minimum 5 years of hand-on experience in data analytics, marketing analytics, or business intelligence within the Retail, eCommerce, or Consumer Goods (FMCG) industries.
• Deep operational familiarity with complex consumer data across multiple digital marketing domains:
  • Digital Media Scopes: Practical knowledge of ad manager structures, attribution models, pixel tracking, and custom audience pipelines (Lookalike/Suppression) across Meta, TikTok, and Google.
  • Social & Search Listening: Experience working with search analytics tools and influencer tracking data metrics.
  • Primary Research Data: Proven capability in handling, weighting, and processing raw survey datasets (Crosstabs, SPSS outputs, or raw survey CSVs).

Technical Skill Set

• Visualization Mastery: Expert-level mastery of Power BI and Tableau (including advanced DAX, Power Query, LOD calculations, and cross-source data blending & optimizing dashboard performance).
• Data Integration & ETL: Robust experience writing scripts (SQL, Python (a plus) ) and utilizing data tools to build automated data pipelines via RESTful APIs and webhooks.
• AI Tooling: Demonstrated experience leveraging AI coding/data tools to optimize workflow efficiency and data transformation pipelines.

Soft Skills & Language

• Ability to work independently as a solo technical contributor who can bridge the gap between technical data engineering and commercial marketing strategy.
• Strong communication skills to support non-technical business users on dashboard logic and inquiries.
• Ability to distill & integrate complex data sets across various business domain and provide solutions on the analytics needs.
• Fluency in English and Chinese (Mandarin) is required to work seamlessly across various teams.