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1,051
Data Scientist jobs in Singapore
Analytics Engineer- Data Operations & Governance
Medium
Singapore
On-site
SGD 70,000 - 90,000
30+ days ago
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Analytics Engineer- Data Operations & Governance
Medium
Singapore
On-site
SGD 60,000 - 90,000
30+ days ago
AI Data Specialist ( Trainee/Part Time)
PIXEL1 PTE. LTD.
Singapore
On-site
SGD 60,000 - 80,000
30+ days ago
Discover more opportunities than anywhere else. Find more jobs nowSemiconductor Process Engineer – Data-Driven Problem Solver
Micron Technology, Inc
Singapore
On-site
SGD 60,000 - 85,000
30+ days ago
Connect with headhunters to apply for similar jobsComputer Vision Engineer (Machine Learning)
DCONSTRUCT ROBOTICS PTE. LTD.
Singapore
On-site
SGD 60,000 - 80,000
30+ days ago
Senior Full-Stack Engineer — Data Viz & SaaS UI
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Singapore
On-site
SGD 70,000 - 90,000
30+ days ago
Data Engineer (1 Year Contract Renewable)
MORGAN MCKINLEY PTE. LTD.
Singapore
On-site
SGD 100,000 - 140,000
30+ days ago
ASUS AICS SG - Machine Learning Engineer
ASUS GLOBAL PTE. LTD.
Singapore
On-site
SGD 80,000 - 120,000
30+ days ago
Senior Data Analyst (Planning and Inventory)
Danaher Corporation
Singapore
On-site
SGD 70,000 - 90,000
30+ days ago
Data Engineer
EXODUSPOINT CAPITAL MANAGEMENT SINGAPORE, PTE. LTD.
Singapore
On-site
SGD 60,000 - 90,000
30+ days ago
Machine Learning Engineer
PLUANG TECHNOLOGIES PTE. LTD.
Singapore
On-site
SGD 50,000 - 70,000
30+ days ago
Senior Data Engineer: Databricks, PySpark & AWS ETL Expert
COMBUILDER PTE LTD
Singapore
On-site
SGD 70,000 - 100,000
30+ days ago
Machine Learning Engineer II - Message Security Products
Menlo Ventures
Singapore
On-site
SGD 70,000 - 100,000
30+ days ago
Data Analyst
ASTEK SINGAPORE INNOVATION TECHNOLOGY PTE. LTD.
Singapore
On-site
SGD 60,000 - 80,000
30+ days ago
Analytics Engineer- Data Operations & Governance
Medium
Singapore
On-site
SGD 70,000 - 90,000
Full time
30+ days ago
Job summary
A leading tech company in Singapore seeks a Data Engineer to manage data operations and ensure the quality of product and user-event data. You will develop robust data pipelines, oversee data governance practices, and collaborate with cross-functional teams. Strong SQL skills and experience with data engineering tools like dbt and Airflow are essential. Join us to optimize data workflows and enhance operational efficiency.
Qualifications
- Strong SQL and proficiency in Python or JavaScript for data infrastructure.
- Track record in designing data governance practices in product analytics.
- Ability to debug pipeline failures and ensure continuity in reporting.
Responsibilities
- Ensure accuracy, reliability, and structure of product and user-event data.
- Build and maintain scalable data pipelines using tools like dbt and Airflow.
- Develop and maintain internal data tools and automate workflows.
Skills
Strong SQL
Python
Data governance practices
Collaboration & Communication
Tools
dbt
Airflow
Git
Job description
Responsibilities:
- Data Operations & Governance: Own the accuracy, reliability, and structure of product and user-event data through robust governance practices; Define and enforce standards for event tracking, data schemas, and documentation across teams; Conduct regular audits, validation checks, and coordinate instrumentation changes with engineering and product teams.
- Data Pipeline Development & Maintenance: Build and maintain scalable, observable data pipelines using tools like dbt, Airflow, or similar frameworks; Monitor pipeline health, implement alerting systems, and resolve data issues with root cause analysis; Optimize pipeline performance and ensure high availability of core datasets for analytics and reporting.
- Internal Tooling & Automation: Develop and maintain internal data tools, utilities, and dashboards using SQL, Python, and lightweight web technologies; Automate workflows to reduce manual reporting and improve operational efficiency for data stakeholders; Create reusable data models that support fast iteration and confident self-service analysis.
- Competitive Intelligence & Data Collection: Operate and enhance data scraping workflows to collect structured information on competitors, pricing, and market trends; Ensure scraping systems are stable, maintainable, and compliant with data privacy and ethical standards.
Requirements:
- Engineering Foundation: Strong SQL and working proficiency in Python or JavaScript for building and maintaining data infrastructure; Experience with modern data engineering tools (e.g., dbt, Airflow, Fivetran, Dagster); Familiarity with version control (Git), code modularization, and documentation practices.
- Data Quality & Governance Experience: Track record designing or maintaining data governance practices in product analytics environments (e.g., Segment, GA4, Mixpanel); Comfortable building QA checks, anomaly detection, and data validation processes; Familiarity with data governance education and data governance related stakeholder management.
- Operational Mindset: Comfortable being on point for data issues, debugging pipeline failures, and ensuring continuity in reporting and dashboards; Ability to set up alerting/logging mechanisms to proactively detect and respond to data problems.
- Collaboration & Communication: Strong written and verbal communication skills to align with product, engineering, and business teams; Able to translate business questions into engineering requirements and technical work into stakeholder-friendly language.
- Preferred Qualifications: Prior experience / knowledge on data science / machine learning; Prior experience on hands-on data engineering; Understanding of data operation & governance in analytics workflows; Experience supporting data for experimentation or A/B testing pipelines.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.