Senior Data Engineer - Cloud Pipelines, CI/CD & Leadership

Epergne Solutions; Singapore; On-site; SGD 112,000 - 155,000; Full time

Job summary

Epergne Solutions is seeking an experienced Data Engineer to design, develop and maintain scalable data solutions using Python and SQL in enterprise environments. You will build robust data pipelines and collaborate with cross‑functional teams across locations.

The role requires 5+ years of hands‑on experience, expertise with libraries like NumPy, pandas, Selenium, and familiarity with AWS S3 and Azure Databricks.

Qualifications

• 5+ years of hands-on experience in Python scripting and application development.
• Strong proficiency in SQL and PostgreSQL.
• Familiarity with Python-based libraries: NumPy, pandas, BeautifulSoup, Selenium, pdfplumber, Requests, etc.
• Knowledge of DevOps tools: CI/CD, Jenkins, Git.
• Experience with AWS (S3) and Azure Databricks.
• Understanding of Agile/Scrum development processes.
• Excellent leadership, communication, and team coordination skills.

Responsibilities

• Design, develop, and maintain scalable data solutions using Python and SQL in enterprise environments.
• Build and automate data pipelines using libraries such as NumPy, pandas, BeautifulSoup, Selenium, and pdfplumber.
• Collaborate with cross-functional teams across multiple locations and time zones.
• Implement CI/CD processes using Jenkins and Git for continuous integration and deployment.
• Work with AWS (S3) and Azure Databricks for cloud-based data management and analytics.
• Deliver projects following Agile and Scrum methodologies.
• Lead and mentor team members to ensure adherence to best practices and quality standards.

Skills

Python scripting

SQL

PostgreSQL

Agile Scrum

Leadership

Communication

Tools

NumPy

pandas

BeautifulSoup

Selenium

pdfplumber

Requests

Jenkins

Git

AWS S3

Azure Databricks

CI/CD

Job description

Epergne Solutions is seeking an experienced Data Engineer to design, develop and maintain scalable data solutions using Python and SQL in enterprise environments. You will build robust data pipelines and collaborate with cross‑functional teams across locations.

The role requires 5+ years of hands‑on experience, expertise with libraries like NumPy, pandas, Selenium, and familiarity with AWS S3 and Azure Databricks.