The objective of the position is to manage the extract/transform/load processes ensuring the data availability.
Responsibilities
- Design, create, modify extract/transform/load (ETL) pipelines in Azure Data Factory ensuring efficient data flow from source to destination.
- Ensure data accuracy and data integrity throughout the ETL processes via data validation, cleansing, deduplication, and error handling to ensure reliable and usable data being ingested.
- Monitor the ETL processes and optimize ETL pipelines for speed and efficiency, addressing bottlenecks, and ensuring the ETL system can handle the volume, velocity, and variety of data.
- Participate in data modeling, designing of the data structures and schema in the data warehouse to optimize query performance and align with business needs.
- Work closely with Business controlling, data engineers and IT teams to understand data requirements and deliver the data infrastructure that supports business goals.
- Provide technical support for ETL systems, troubleshooting issues and ensuring the continuous availability and reliability of data flows.
- Ensure proper documentation of data sources, ETL processes and data architecture.
Requirement
- Minimum 5-7 years of database experience in an enterprise production environment
- Working experience on Azure cloud and with Azure Data Factory is a must, and Oracle cloud would be an advantage
- Bachelor’s in information technology or equivalent
- Demonstrable proficiency in PL/SQL to write SQL scripts
- Experience in data injection, cleansing and data modelling
- Hands on Database administration skills on Oracle and PostgreSQL would be an advantage
- Good analytical and troubleshooting skills
- Curious, proactive, self-motivated and able to work in a dynamic environment
Interested candidates may apply through the application system or send it to [email protected]. Shortlisted candidates will be notified.
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Morgan McKinley Pte Ltd
Dinu Dinesh
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