Analytics Engineer / Senior Analytics Engineer
Position: Analytics Engineer / Senior Analytics Engineer
Level:
- Mid-Level or Senior (Open based on depth of experience)
Location:
- Kuala Lumpur, Malaysia (Hybrid) 50% office
Role Type:
- 100% Individual Contributor (IC)
Target Environment:
- Data-First Tech Product / Commercial SaaS Company
Role Overview:
This role sits at the intersection of Data Engineering and Data Science. As an Analytics Engineer, you will transform messy, ambiguous data ecosystems into clean, trusted analytics layers that directly fuel high-stakes commercial software applications for global corporate and enterprise B2B customers. The focus is on combining software rigor with deep business logic to deliver actionable insights.
Core Responsibilities:
- Transform ambiguity into architecture by independently structuring, validating, and breaking down vague commercial goals or unorganized datasets.
- Develop, test, and iterate on custom analytical logic and business-critical algorithms (e.g., anomaly detection, data cleansing, tracking patterns), stress-testing and verifying assumptions.
- Design end-to-end data models, including schema design (such as Star Schemas), building robust data pipelines, and establishing data quality boundaries.
- Extract commercial value by interpreting data in the context of enterprise client operations, ensuring outputs provide actionable business insights.
- Act as a technical bridge between Product Management, backend engineering, and data platform operations to scale commercial data tracking and forecasting products.
Tech Stack:
- Advanced proficiency in Python (programming and scripting).
- Exposure to Databricks and PySpark is highly preferred (can be learned on the job with strong Python skills).
- Advanced SQL, database normalization, schema architecture, and familiarity with version control systems (Git).
About You: Who is the Ideal Fit for this Role?
Mindset & Behavior:
- Analytical thinker with a natural curiosity and a drive to validate algorithms and cross-check assumptions.
- Comfortable with ambiguity and chaos, taking ownership of vague prompts and independently structuring solutions.
- Experience in a data-driven Product company, technology scale-up, or commercial SaaS enterprise, understanding how data transformations impact user-facing applications.
- Flexible professional titles: Analytics Engineer, Data Engineer, Data Scientist, or Senior Data Analyst, with a strong background in hands-on data analysis, pipeline manipulation, and programmatic problem-solving.
Educational & Rigor Blueprint:
- Elite quantitative mindset, likely supported by a formal degree in Mathematics, Statistics, Actuarial Science, Computer Science, or Software Engineering.
- Comfortable working with dense, multi-dimensional numerical frameworks.
Who This Job is NOT Right For:
- Pure Business Intelligence / Dashboard Builders: If your experience is limited to building executive charts in PowerBI, Tableau, or Looker Studio, this role is too engineering-heavy.
- Pure Data Engineers: If you focus solely on infrastructure, database administration, or basic data orchestration without interest in commercial context or business logic, this role is too analytical.
- Pure Data Scientists: If you are focused on theoretical models or academic research without a desire to build production-grade, repeatable pipelines, this environment is too execution-focused.
- Career IT / Management Consultants: If your experience is limited to short-term consulting projects without long-term product ownership or scaling challenges, this team is not a match.
Why Join Us?
You will have true product ownership, working alongside a premier international engineering hub in Kuala Lumpur and collaborating directly with senior data leaders. The systems you build will power high-stakes commercial platforms, influencing multi-million-dollar operational decisions for major enterprise clients. Bureaucracy is minimized, and talented developers are empowered to make a direct impact.