Cloud Engineering

Helius Technologies Pte Ltd; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Helius Technologies Pte Ltd in Singapore is seeking a Cloud Data Engineer with 4–5 years of hands-on experience to build, maintain, and optimize a scalable, secure data infrastructure. You will leverage AWS for storage and compute, Databricks for high‑performance data processing, and Informatica IDMC for data integration, governance and quality.

The role requires strong SQL and Python/Scala for Spark processing, experience designing ETL/ELT pipelines, and implementing data governance best

Qualifications

• 4–5 years hands-on experience with data systems.
• Strong SQL and Python/Scala for Spark processing.
• Experience with AWS, Databricks and Informatica IDMC.
• Knowledge of ETL/ELT design and data governance best practices.

Responsibilities

• Data Pipeline & ETL Development using AWS Glue/Lambda and Databricks.
• Storage & Platform Optimization for data lakes and warehouses.
• Data Integration & Quality using Informatica IDMC.
• Security & Governance across AWS and Databricks.
• Automation & Workflow Management with cloud services.

Skills

SQL

Python/Scala

ETL/ELT

Data Governance

Data Pipelines

Tools

AWS

Databricks

Informatica IDMC

Job description

We are looking for a Cloud Data Engineer (4–5 years experience) to build, maintain, and optimize a scalable and secure data infrastructure. The candidate will leverage AWS for cloud storage/compute, Databricks for high-performance data processing, and Informatica IDMC for data integration, governance, and quality management.

Key Responsibilities

• Data Pipeline & ETL Development: Design and automate scalable data pipelines (ingestion, processing, transformation) using AWS (Glue, Lambda), Databricks (Spark, Delta Lake), and Informatica IDMC.
• Storage & Platform Optimization: Manage and optimize data lakes, warehouses, and databases (S3, RDS, Redshift, DynamoDB) for performance and cost efficiency.
• Data Integration & Quality: Integrate diverse internal and external data sources using Informatica IDMC to ensure data consistency, lineage, cataloging, and high quality.
• Security & Governance: Implement security standards, data encryption, access controls, and data privacy compliance across AWS and Databricks.
• Automation & Workflow Management: Automate routine data processing and monitoring using AWS Step Functions, Lambda, Databricks Jobs, and Informatica workflows.

Requirements / Qualifications

• Experience: 4 to 5 years of hands-on experience in developing, implementing, and maintaining IT data systems.
• Tech Stack Expertise:
• AWS: S3, Redshift, RDS, DynamoDB, Glue, Lambda, Step Functions.
• Databricks: Apache Spark, Delta Lake, Databricks Jobs.
• Integration & Governance: Informatica IDMC (CDI, CDQ, Data Cataloging).
• Core Skills: Strong SQL, Python/Scala for Spark processing, ETL/ELT pipeline design, and data governance best practices.