Analytics Engineering Lead - Data Platform & AI

pluang technologies pte. ltd.; Singapore; Hybrid; SGD 120,000 - 170,000; Full time

Benefits offered by this job

Health & Wellness

Financial Well-being

Career Development

Flexibility & Time Off

Job summary

Pluang Technologies Pte. Ltd. is seeking an analytics engineer to own the release process, data warehouse to AI connections, and the pipelines that keep AI workspaces current. You will build the first in‑house agent on top of that foundation and ensure downstream tools stay accurate.

You will collaborate with domain analysts and engineers to deliver production‑grade data models, tests, and documentation, using dbt, BigQuery, Airflow, and LLM APIs, with a strong focus on reliability and security.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Statistics, or related field.
• 5+ years in analytics engineering or data engineering with production delivery experience.
• Strong Python for production scripting, pipelines, and API integration.
• Experience with modern data transformation framework (dbt) including modeling, docs, tests, and CI/CD.
• SQL proficiency with BigQuery or equivalent cloud warehouse and complex transformations.

Responsibilities

• Own the release process and change management for data pipelines and AI integration.
• Build data and document ingestion pipelines to feed AI workspaces.
• Ensure data models meet quality with docs, tests, and PR gates.
• Implement validation and monitoring to detect issues before production.
• Collaborate with domain analysts and engineers to deliver production-grade reporting.

Skills

Python production scripting

SQL proficiency

CI/CD

Airflow

LLM APIs

Software engineering practices

Cross-team collaboration

Effective communication

OpenAI/Anthropic familiarity

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

dbt

BigQuery

Airflow

LangChain/LangGraph

OpenAI API / AI tools

Job description

Pluang Technologies Pte. Ltd. is seeking an analytics engineer to own the release process, data warehouse to AI connections, and the pipelines that keep AI workspaces current. You will build the first in‑house agent on top of that foundation and ensure downstream tools stay accurate.

You will collaborate with domain analysts and engineers to deliver production‑grade data models, tests, and documentation, using dbt, BigQuery, Airflow, and LLM APIs, with a strong focus on reliability and security.