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Data Solution Specialist
2 weeks ago
Company:
Pillar of Global Finance
Location:
Kuala Lumpur
Job Requirements:
- The Data Engineer is responsible for architecting, implementing, and maintaining robust data pipelines that support various AI and ML initiatives within the bank.
- Collaborate with internal and external stakeholders to identify and acquire relevant data sources for AI/ML projects, leveraging on both structured and unstructured data to enrich the organization's data assets.
- Develop and implement strategies for ingesting, cleansing and transforming data into designated data repositories, ensuring data quality, consistency and integrity throughout the process.
- Design and develop reusable and scalable data assets, including data models, pipelines, and workflows, that support the organization's AI ML initiatives.
- Provide support and guidance to data analysts and data scientists in accessing, understanding and utilizing the data assets effectively for analytics and modelling purposes, optimizing the execution of AI ML algorithm and workflow.
- Monitor and troubleshoot data pipelines, identifying and resolving issues to ensure uninterrupted data flow.
Responsibilities:
- Bachelor's degree in computer science, data science, engineering or related field
- Proven experience in data acquisition, ingestion and management, preferably in a data engineering role
- Strong understanding of data modelling, data warehousing and data integration concepts and best practices
- Proficiency in SQL, Python for data manipulation and analysis
- Data modelling and schema design.
Hard Skills
- Soft Skills Required Tool and Program Proficiency
- ETL (Extract, Transform, Load) processes and tools.
- Version control systems (e.g., Git).
- Database management and optimisation techniques.
- Strong problemsolving skills and attention to detail, with a proactive and results oriented approach
- Ability to work independently in a fast paced and dynamic environment
- Excellent communication and interpersonal skills with the ability to collaborate effectively with technical and non technical stakeholders
- Apache Hadoop, Apache Spark, Apache Kafka, AWS/GCP/Azure services, SQL and NoSQL databases, Python/Java/Scala
- Git version control
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