Executive recruitment company Monroe Consulting Group Philippines is recruiting on behalf of a leading player in the global technology landscape with a robust presence in areas such as e-commerce, cloud solutions, digital content delivery, and advanced artificial intelligence applications.
Our respected client is currently seeking an exceptionally talented, visionary, and deeply focused BI Engineer with outstanding analytical skills for the role of Business Intelligence Engineer, Data Analytics.
The Business Intelligence Engineer, Data Analytics will build some of the largest reporting objects in the Accounts Receivable BI space, thereby contributing to business outcomes by analytics. This is a unique opportunity to build one of the largest Finance Operations BI environments of present day. The company is located in Pasay City, Philippines, with Hybrid work-setup.
Key job responsibilities:
- Solve real life business problems by data analytics using big data
- Collaborate with business users on requirements, objectives and measures
- Optimize and organize data pipelines from the Finance Operations Data Lake into the visualization environment
- Build and manage Tableau workbooks
- Provide input and recommendations on technical issues to data engineering and software engineering teams
- Contribute to data design, data modelling and data extracts/transforms
- Work in a genuinely global environment, across various functional teams
Key job requirements:
- 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc.
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience writing complex SQL queries
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets