Cloud Data Engineer: Build Scalable ETL Pipelines

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Optimum Solutions (Singapore) Pte Ltd is seeking a data engineer to design and maintain production-grade data pipelines. You will clean and transform data, build ETL processes, and ensure data accuracy across systems using SQL, Python, and cloud services.

You will work with various databases and big data tools, implement scalable data architectures, and collaborate with engineering and analytics teams to bridge the gap between data engineering and business insights.

Qualifications

• Proficient in data cleaning and transformation using SQL, pandas, R.
• Experience building ETL pipelines (SSIS, AWS DMS, Python, AWS Lambda, ECS, EventBridge, AWS Glue).
• Proficient in database design and multiple databases (SQL, PostgreSQL, AWS S3, Athena, MongoDB, MySQL, SQLite).
• Experience with cloud platforms (AWS, Azure, Google Cloud).
• Experience in big data environments and data pipelines (ETL/ELT).
• Knowledge of system design, data structures and algorithms.
• Familiar with data modelling, data access, and storage like Data Lake/Warehouse.
• Familiar with REST APIs and web protocols.
• Familiar with big data frameworks (Hadoop, Spark, Kafka, RabbitMQ).
• Familiar with web scraping tools (Beautiful Soup, CasperJS, PhantomJS, Selenium, Node.js).
• Familiar with data governance and security practices.
• Comfortable in SQL/Python scripting and Windows/Linux environments.
• Interest in bridging engineering and analytics.

Skills

SQL

Python

Data cleaning

ETL pipelines

Data modelling

Big data

REST APIs

AWS

Scripting

Windows/Linux

Tools

SSIS

AWS DMS

AWS Lambda

ECS

EventBridge

AWS Glue

Beautiful Soup

Selenium

CasperJS

PhantomJS

Node.js

Job description

Optimum Solutions (Singapore) Pte Ltd is seeking a data engineer to design and maintain production-grade data pipelines. You will clean and transform data, build ETL processes, and ensure data accuracy across systems using SQL, Python, and cloud services.

You will work with various databases and big data tools, implement scalable data architectures, and collaborate with engineering and analytics teams to bridge the gap between data engineering and business insights.