Data Engineer VMA

Tech Aalto Pte ltd; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

Tech Aalto Pte ltd is seeking a Data Engineer in Singapore to design, build and deploy data tables, views and data marts across warehouses, lakes and marts. You will extract, clean, transform and load data while enabling scalable data pipelines for batch and real-time processing.

The role requires strong SQL, Python, ETL tools, cloud skills (AWS) and experience with data modelling, APIs and big data frameworks.

Qualifications

• Proficient in data cleaning and transformation to ensure accuracy and consistency.
• Experienced in building production-grade ETL pipelines using SQL Server SSIS, AWS DMS and related tooling.
• Strong database design skills across SQL, NoSQL and cloud storage like S3.
• Hands-on with cloud platforms (AWS) and data engineering on large data sets.
• Knowledge of data modelling, data access and scalable storage architectures.
• Familiar with RESTful APIs and web requests/protocols.
• Experience with big data frameworks and tools (Spark, Hadoop, Kafka).
• Comfortable with scripting languages (SQL, Python) on Windows and Linux.

Responsibilities

• Design, develop and deploy data tables, views and marts in data warehouses, ODS, data lake and data virtualization.
• Perform data extraction, cleaning, transformation, and flow; web scraping may be part of the scope.
• Build and maintain large-scale batch and real-time data pipelines using processing frameworks.
• Integrate data silos in scalable and compliant ways.
• Collaborate with Project Manager, Data Architect, Analysts and Developers to build data driven products.
• Develop backend APIs and work on databases to support applications.
• Operate in an Agile environment with CI/CD practices and code reviews.

Skills

Data cleaning

ETL pipelines

Database design

Cloud technologies

Data modelling

REST APIs

Big data tools

Web scraping

Scripting languages

Windows/Linux

Tools

SQL

SSIS

Python

AWS Lambda

AWS Glue

AWS DMS

ECS

S3

Job description

• Design, develop and deploy data tables, views and marts in data warehouses, operational data store, data lake and data virtualization.


• Perform data extraction, cleaning, transformation, and flow. Web scraping may be also a part of the work scope in data extraction.


• Design, build, launch and maintain efficient and reliable large‑scale batch and real‑time data pipelines with data processing frameworks.


• Integrate and collate data silos in a manner which is both scalable and compliant.


• Collaborate with Project Manager, Data Architect, Business Analysts, Frontend Developers, Designers and Data Analyst to build scalable data driven products.


• Be responsible for developing backend APIs & working on databases to support the applications.


• Work in an Agile Environment that practices Continuous Integration and Delivery.


• Work closely with fellow developers through pair programming and code review process.

Data Engineer

Responsibility

• Design, develop and deploy data tables, views and marts in data warehouses, operational data store, data lake and data virtualization.


• Perform data extraction, cleaning, transformation, and flow. Web scraping may be also a part of the work scope in data extraction.


• Design, build, launch and maintain efficient and reliable large‑scale batch and real‑time data pipelines with data processing frameworks.


• Integrate and collate data silos in a manner which is both scalable and compliant.


• Collaborate with Project Manager, Data Architect, Business Analysts, Frontend Developers, Designers and Data Analyst to build scalable data driven products.


• Be responsible for developing backend APIs & working on databases to support the applications.


• Work in an Agile Environment that practices Continuous Integration and Delivery.


• Work closely with fellow developers through pair programming and code review process.

Experience and Skills Needed

• Proficient in general data cleaning and transformation (e.g. SQL, pandas, R, etc) to ensure data accuracy and consistency.


• Proficient in building ETL pipeline (eg. SQL Server Integration Services (SSIS), AWS Database Migration Services (DMS), Python, AWS Lambda, ECS Container task, Event bridge, AWS Glue, Spring).


• Proficient in database design and various databases (e.g. SQL, PostgreSQL, AWS S3, Athena, mongodb, postgres/gis, mysql, sqlite, voltdb, cassandra, etc).


• Experience in cloud technologies such as GPC, GCC (i.e. AWS, Azure, Google Cloud).


• Experience and passion for data engineering in a big data environment using Cloud platforms such as GPC, GCC (i.e. AWS, Azure, Google Cloud).


• Experience with building production‑grade data pipelines, ETL/ELT data integration.


• Knowledge about system design, data structure and algorithms.


• Familiar with data modelling, data access, and data storage infrastructure like Data Mart, Data Lake, Data Virtualisation and Data Warehouse for efficient storage and retrieval.


• Familiar with rest api and web requests/protocols in general.


• Familiar with big data frameworks and tools (eg. Hadoop, Spark, Kafka, RabbitMQ).


• Familiar with W3C Document Object Model and customized web scraping (e.g. Beautiful Soup, CasperJS, PhantomJS, Selenium, Nodejs, etc).


• Familiar with data governance policies, access control and security best practices.


• Comfortable in at least one scripting language (eg. SQL, Python).


• Comfortable in both windows and linux development environments.