Senior Data Engineer
Posted Updated
Summary
Senior Data Engineer in Singapore designing scalable data pipelines with Databricks on AWS and PySpark, handling ingestion, transformation, cleansing, and ETL automation, potentially refactoring Informatica DEI workflows, while supporting analytics and data science teams.
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
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