Data Engineer
7 days ago
Job Title: Data Engineer
Location: Bangsar South, Kuala Lumpur
Responsibilities
- Design, develop, and maintain interactive Power BI dashboards and reports, with strong focus on automation, user experience, and data storytelling.
- Translate complex business requirements into effective data visualizations and reporting solutions.
- Integrate and manage data from financial platforms such as Aladdin and Refinitiv, ensuring data quality, consistency, and availability.
- Build and optimize data pipelines using Azure Data Factory, Azure Databricks, and other Azure cloud services.
- Perform large-scale data processing and transformation using SQL, Python, and PySpark.
- Support data ingestion into Azure Analysis Services and maintain structured data in the organization's Data Lake.
- Implement and enforce data quality standards, best practices, and maintain fully documented technical procedures.
- Stay updated on advancements in Power BI, Azure, and modern data engineering technologies to drive innovation.
- Collaborate closely with project teams and business users; provide support and handle ad hoc development tasks as needed.
Requirements
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- 3–5+ years of experience in data science, with at least 2–3 years of hands-on experience in data engineering or backend data workflows.
- Proficient in Azure Data Factory, Azure Databricks, Azure SQL, and Unity Catalog.
- Strong practical experience with SQL, Python, and PySpark for data manipulation and transformation.
- Solid expertise in Power BI, including DAX, data modeling, and custom visual development.
- Familiarity with Azure Analysis Services and experience in performance tuning.
- Strong analytical, problem-solving, and troubleshooting skills with emphasis on data accuracy and reliability.
Job Type: Full-time
Pay: RM5, RM6,000.00 per month
Experience:
- Power BI, including DAX, data modeling: 1 year (Preferred)
- data science: 2 years (Preferred)
- data engineering or backend data workflows.: 2 years (Required)
- Azure Data Factory, Azure Databricks, Azure SQL: 2 years (Preferred)
- SQL, Python, and PySpark : 2 years (Preferred)
Work Location: In person
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