Senior Data Engineer

Cadenza Solutions; Singapore; On-site; SGD 140,000 - 210,000; Full time

Job summary

Cadenza Solutions is seeking a Senior Data Engineer to build scalable data pipelines, perform complex transformations, and support analytics workloads. The ideal candidate has hands-on Databricks on AWS, PySpark, and Python experience, with ETL orchestration and automation skills, plus a track record of delivering high-quality data for reporting and modeling across teams.

Strong communication in client-facing environments and the ability to refactor Informatica DEI workflows into Databricks when

Qualifications

• Minimum 8 years of experience in Data Engineering.
• Strong proficiency in Databricks on AWS, PySpark, and Python.
• Experience with ETL development, data transformations, data quality frameworks, and pipeline automation.

Responsibilities

• Design and implement robust, scalable data pipelines using Databricks on AWS and PySpark.
• Perform data ingestion, transformation, cleansing, and validation from various sources.
• Collaborate with analytics and data science teams to deliver high-quality data for reporting and modeling.
• Understand and translate Informatica DEI workflows into Databricks-based implementations (if applicable).
• Optimize and automate ETL workflows for performance and cost-efficiency.
• Ensure data quality, lineage, and governance are upheld in all solutions.

Skills

Databricks on AWS

PySpark

Python

ETL development

Data transformations

Data quality frameworks

Communication (client-facing)

Tools

Informatica DEI

Job description

Role Overview :

• We are seeking a highly skilled Senior Data Engineer with a strong background in building scalable data pipelines, performing complex data transformations, and enabling analytics workloads.
• The ideal candidate should have hands-on experience with Databricks on AWS, PySpark, and Python, with a working understanding of ETL orchestration and automation.
• Familiarity with Informatica DEI is a plus, as the role may involve refactoring existing Informatica workflows into PySpark.

Key Responsibilities:

• Design and implement robust, scalable data pipelines using Databricks on AWS and PySpark
• Perform data ingestion, transformation, cleansing, and validation from various sources
• Collaborate with analytics and data science teams to deliver high-quality data for reporting and modeling
• Understand and translate Informatica DEI workflows into Databricks-based implementations (if applicable)
• Optimize and automate ETL workflows for performance and cost-efficiency
• Ensure data quality, lineage, and governance are upheld in all solutions Required Skills & Experience:
• Minimum 8 years of experience in Data Engineering
• Strong proficiency in Databricks on AWS, PySpark, and Python
• Solid experience in ETL development, data transformations, cleaning, data quality frameworks/standards, and pipeline automation
• Understanding of data quality principles and performance tuning techniques Familiarity with Informatica DEI is a nice to have
• Excellent communication skills in client-facing environments

2. SKILLS

Data Engineering, Data Science, ETL, Informatica, Java