Intern, Data Engineering and Automation (PNPL)
An intern at Phillip Nova (PhillipCapital) supporting the firm's financial-services data infrastructure: building, optimizing, and documenting ETL/ELT pipelines, automation, and API integrations using SQL and Python, plus CI/CD for data deployment and LLM/data-warehouse planning.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Intern
- Employment
- Internship
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Undergraduate majoring in Data Science / Statistics / Computer Science / Quantitative Finance / Business Analytics / Economics / Mathematics or other relevant majors
- Proficient in Data modelling, Data Architecture
- Proficient in SQL, Python programming and API integration
- Foundational understanding of Generative AI and LLMs
Nice to have
- Familiarity with CI/CD practices and automated deployment on Git
- Familiar with Microsoft SQL Server tools (SSMS, SSIS)
Full description
Intern, Data Engineering and Automation (PNPL)Job Description:
The Data Engineering and Automation Intern will play a key role in supporting Phillip Nova’s data infrastructure by building, optimizing, and documenting our ETL pipelines and automation solutions. This hands-on position requires proficiency in SQL and Python to design and implement data automation projects, including API integrations and data manipulation scripts, to deliver business-critical solutions in the financial services domain.
Key Responsibilities:
- Propose automation, AI or data engineering solutions based on business needs.
- Build, maintain, and introduce best practices to ETL/ELT pipelines and data transformation jobs in our data warehouse.
- Implement and maintain CI/CD pipelines alongside our testing environment for data solution deployment, ensuring seamless integration.
- Assist in designing and planning LLM and data warehouse implementations.
- Ensure high data quality and data integrity by designing and implementing automated tests and validation rules across all implemented pipelines.
- Help the data team build a catalogue and document the data warehouse.
Requirements:
- Undergraduate majoring in Data Science / Statistics / Computer Science / Quantitative Finance / Business Analytics / Economics / Mathematics / other relevant majors.
- Proficient in Data modelling, Data Architecture.
- Proficient in SQL, Python programming and API integration.
- Foundational understanding of Generative AI and LLMs.
- (Optional) Familiarity with CI/CD practices and automated deployment on Git.
- (Optional) Familiar with Microsoft SQL Server tools (SSMS, SSIS).
We regret that only shortlisted candidates will be notified.
Brought to you by Phillip Nova Pte Ltd (A member of PhillipCapital)