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.