Data Enablement Lead

Lalamove is hiring a Data Enablement Lead. Level rates it ; you can apply on Lalamove.

Level's read on this job

On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include OpenAI and LangChain.
Level classifies it as a lead role.
Level lists 142 other open roles at Lalamove.

AI in this role

openailangchain

We are seeking a versatile, highly motivated Data Enablement Lead to bridge the gap between complex backend data infrastructure and business-facing analytics solutions. In this role, you will be the core engine driving analytics, reporting, and self-service data products for our Business Unit (BU). While our central data infrastructure team handles enterprise-wide platform needs, you will take ownership of our BU's specific data stack—coordinating with the central team to manage existing upstream pipelines while building and maintaining our own localized data pipelines when speed and agility are required. Beyond standard dashboards and data pulls, your goal is to revolutionize how non-technical stakeholders interact with data. You will design next-generation data consumption tools—ranging from high-performance data cubes to AI-driven query bots—empowering our BU to get answers instantly.

What we seek:

Hands-On Engineering & Tooling

Data Pipelines & Backend: Build, maintain, and optimize data pipelines feeding our BU’s analytics layer. Work across our core data platform (Apache Hive) and high-performance OLAP backend (Apache Doris).
Next-Gen Data Tools: Architect non-data-person-facing tools to automate data access, such as setting up data cubes/semantic layers and building AI/LLM-powered data bots (e.g., text-to-SQL / natural language data querying).
Architecture & Standards: Establish best practices for data modeling, pipeline monitoring, and data quality within our BU's local repository

Technical Project Management & Coordination

Cross-Team Collaboration: Act as the primary technical interface between analytics / operational team and the central platform data engineering team.
Project Delivery: Scope, prioritize, and manage the end-to-end lifecycle of analytics engineering projects, translating non-technical needs into clear technical specifications.
Enablement & Stakeholder Management: Educate and support operational team on self-serve tools, documentation, and data literacy initiatives.

What you'll need:

Technical Skills

Data Engineering & Warehousing: 5+ years of experience in data engineering, analytics engineering, or technical data product management.
Stack Expertise: Strong proficiency in SQL and Python. Solid experience with large-scale data warehouses (Apache Hive) and modern OLAP engines (Apache Doris, ClickHouse, StarRocks, or similar).
Data Product & AI Innovation: Demonstrated interest or experience in building interactive data tools (e.g., Cube.js, semantic layers) or leveraging AI/LLM frameworks (e.g., LangChain, OpenAI APIs, Text-to-SQL pipelines) to simplify data retrieval.
Data Modeling: Deep understanding of dimensional modeling, star schemas, data aggregation, and query optimization techniques.

Project & Stakeholder Management

Proven ability to coordinate across cross-functional engineering teams with competing business priorities.
Strong project management skills—able to track dependencies, mitigate risks, and manage stakeholder expectations clearly without micro-managing.
Pragmatic approach to the "Build vs. Coordinate" tradeoff—knowing when to rely on central platforms versus when to build lightweight local solutions.

To all candidates- Lalamove respects your privacy and is committed to protecting your personal data.This Notice will inform you how we will use your personal data, explain your privacy rights and the protection you have by the law when you apply to join us. Please take time to read and understand this Notice. Candidate Privacy Notice: https://www.lalamove.com/en-hk/candidate-privacy-notice

How we rate this

Data Enablement Lead at Lalamove rates 67 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Enablement Lead is an open job at Lalamove.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Hong Kong SAR.
The job was posted on July 24, 2026.
Seniority: lead.
Applications are handled by Lalamove. Apply on Lalamove

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

OpenAILangChain

Questions you could be asked

What's a project where you used OpenAI hands-on?
Walk me through how you've used LangChain in your day-to-day work.
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: OpenAI and LangChain. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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