Insights Data Engineer for Product & Engineering

Dyson; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Dyson is seeking a Data Analytics & Insights Engineer in Singapore to drive data preparation, pipeline management, and dashboard development for engineering and product teams.

You will transform complex data into actionable insights, build end-to-end pipelines across S3, GCS, and BigQuery, and deliver self-service analytics through Tableau or Streamlit.

The role blends data engineering and analytics, requiring strong Python/SQL, cloud platform experience, and excellent stakeholder communication.

Qualifications

• Proven experience in data analytics and data engineering roles.
• Strong Python/SQL skills for data analysis.
• Experience with cloud data platforms (BigQuery, GCP, AWS S3).
• Experience building ETL/data pipelines.
• Experience with Tableau/Streamlit dashboards.
• Excellent stakeholder management and communication.
• Ability to translate business requirements into analytics.

Responsibilities

• Analyze product, engineering, and machine data to generate actionable insights.
• Translate stakeholder requirements into analytical outputs and KPIs.
• Develop Python and SQL analyses to support decision-making.
• Build and maintain end-to-end data pipelines across S3, GCS, and BigQuery.
• Design dashboards and reports in Tableau or Streamlit for self-service analytics.
• Ensure data quality, reliability, and scalable data products.

Skills

Python

SQL

Analytical thinking

Problem solving

Stakeholder management

Communication

Requirements translation

Data storytelling

Tools

BigQuery

GCP

AWS S3

Tableau

Streamlit

ETL pipelines

Job description

Dyson is seeking a Data Analytics & Insights Engineer in Singapore to drive data preparation, pipeline management, and dashboard development for engineering and product teams.

You will transform complex data into actionable insights, build end-to-end pipelines across S3, GCS, and BigQuery, and deliver self-service analytics through Tableau or Streamlit.

The role blends data engineering and analytics, requiring strong Python/SQL, cloud platform experience, and excellent stakeholder communication.