Senior Data Engineer

RAPSYS TECHNOLOGIES PTE. LTD.; Singapore; On-site; SGD 90,000 - 140,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE. LTD. in Singapore is seeking a data engineer to design scalable data pipelines, architectures and reusable data capabilities.

You will work with Engineers, Product Managers, Data Scientists, analysts and users to implement robust data solutions. The role emphasizes reliability, security, observability and performance, with a focus on modern data platforms.

Join a team that champions automated testing, code reviews, CI/CD and infrastructure-as-code while mentoring others.

Qualifications

• Proficient in Python and SQL; strong software engineering practices.
• Experience building and operating complex production data systems.
• Strong enterprise data architecture and engineering experience.
• Experience with data pipelines, data modelling, data warehouses, data lakes and lakehouse architectures.
• Experience with AWS and modern data platforms (Redshift, Snowflake, Databricks, BigQuery).
• Experience with data orchestration, transformation and modelling.
• Strong testing, CI/CD, monitoring, troubleshooting and data quality.

Responsibilities

• Design data pipelines, architectures, models and reusable data capabilities.
• Apply engineering practices to improve reliability, security, observability and performance.
• Evaluate technologies and contribute to data architecture and engineering standards.
• Promote automated testing, code review, CI/CD and infrastructure-as-code.
• Work with engineers, Product Managers, Data Scientists, analysts and users.
• Provide technical leadership through design reviews, mentoring and knowledge sharing.

Skills

Python

SQL

Data engineering

Data modelling

CI/CD

Testing

Monitoring

Data quality

Tools

AWS

Redshift

Snowflake

Databricks

BigQuery

Airflow

Spark

Tableau / Power BI

Terraform

Job description

Key Responsibilities

• Design data pipelines, architectures, models and reusable data capabilities.
• Apply engineering practices to improve reliability, security, observability and performance.
• Evaluate technologies and contribute to data architecture and engineering standards.
• Promote automated testing, code review, CI/CD and infrastructure-as-code.
• Work with engineers, Product Managers, Data Scientists, analysts and users.
• Provide technical leadership through design reviews, mentoring and knowledge sharing.

Requirements

• Strong software engineering skills with Python and SQL.
• Experience building and operating complex production data systems.
• Strong enterprise data architecture and engineering experience.
• Experience with data pipelines, data modelling, data warehouses, data lakes and lakehouse architectures.
• Experience with AWS and modern data platforms such as Redshift, Snowflake, Databricks or BigQuery.
• Experience with data orchestration, transformation and modelling.
• Strong understanding of testing, CI/CD, monitoring, troubleshooting and data quality.

Good to Have

• Apache Airflow or equivalent.
• Apache Spark.
• AWS data services and cloud infrastructure.
• Tableau, Power BI or equivalent.
• Infrastructure-as-code, data observability, metadata, catalogue or lineage.