Data Engineer (Financial/investment domain)

MANPOWER STAFFING SERVICES (SINGAPORE) PTE LTD; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A tech staffing agency in Singapore is seeking a skilled Data Engineer to join their Data & Analytics team. The role involves designing and maintaining data pipelines using Snowflake and SQL, focusing on investment reporting data. Applicants should have 2-5 years of experience in data engineering along with a solid understanding of financial concepts and data governance practices. Ideal candidates will be proficient in SQL and familiar with ETL processes.

Qualifications

• 2-5 years of experience in data engineering, focused on SQL and data manipulation.
• Experience with cloud-based data warehousing solutions like Snowflake.
• Understanding of investment operations and portfolio management concepts.

Responsibilities

• Design, implement, and maintain data pipelines using Snowflake and SQL.
• Collaborate with stakeholders to understand data requirements.
• Optimize data performance and monitor pipelines.

Skills

Snowflake SQL

Data manipulation

Investment reporting knowledge

Python

ETL processes

Data governance best practices

Education

Bachelor's degree in Computer Science or related field

Tools

Tableau

Qlikview

Qliksense

Job description

Project Description

We are seeking a highly skilled and experienced Data Engineer to join our Data & Analytics team. The ideal candidate will have a solidbackground in Snowflake SQL, investment reporting data, and financial knowledge related to investment management. As a Data Engineer, you will play a critical role in designing, implementing, and maintaining our data infrastructure to support investment reporting and analytics.

Responsibilities

• Data Infrastructure Development
  1. Design, implement, and maintain scalable and efficient data pipelines using Snowflake and SQL.
  2. Develop data models, ETL processes, and data integration workflows to ensure high data quality and reliability.
  3. Optimize data storage and retrieval performance in Snowflake.
• Data Manipulation and Transformation
  1. Perform complex data manipulation and transformation using SQL to prepare data for analysis and reporting.
  2. Implement data cleansing, aggregation, and enrichment processes to ensure data accuracy and consistency.
  3. Develop and maintain reusable SQL scripts and stored procedures for data processing.
• Collaboration and Support
  1. Collaborate with data analysts and other stakeholders to understand data requirements and deliver solutions that meet their needs.
  2. Provide technical guidance and mentorship to junior data engineers and other team members.
  3. Work closely with IT and DevOps teams to ensure seamless data integration and deployment.
• Data Layer Preparation
  1. Design and build data layers to support various analytical and reporting needs.
  2. Ensure data layers are well-documented, easily accessible, and performant.
  3. Implement data governance and security best practices to protect sensitive information.
• Performance Tuning and Optimization
  1. Monitor and optimize the performance of data pipelines, databases, and queries.
  2. Identify and resolve performance bottlenecks to ensure timely and efficient data processing.
  3. Stay up-to-date with the latest trends and best practices in data engineering and apply them to improve our data infrastructure.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
• Minimum of 2-5 years of experience in data engineering, with a deep focus on SQL and data manipulation.
• Proven experience working with Snowflake or other cloud-based data warehousing solutions.
• Solid background in designing data model and building scalable data pipelines and data models.
• Solid understanding of financial instruments, investment operations, investment reporting and portfolio management concepts.
• Knowledge of investment performance measurement, risk analysis, and portfolio management concepts.
• Expert-level proficiency in SQL, with the ability to write complex queries and optimize them for performance.
• Proven experience with ETL tools and processes.
• Familiarity with Tableau, Qlikview, Qliksense
• Familiarity with programming such as Python.
• Knowledge of data governance, security, and compliance best practices.