Business Intelligence Engineer

Role: Business Intelligence Engineer

Start: ASAP

Location: London

Pay: £310 per day + Holiday Pay

Expected duration: 6 months

Our client is a global tech business. They are looking for a business intelligence analyst to join their team.

This role is within Global Tax Services to support Indirect Tax Audits and work in support of Audit Readiness. As part of audit team responsibilities includes:

Supporting indirect Tax team on Tax audit on daily basis

• Diving deep into the details to develop meaningful findings and provide required data
• Interfacing with Tax, Finance and Accounting customers, gathering requirements, and delivering solutions
• Analysing and solve problems at their root, stepping back to understand the broader context
• Learn and understand a broad range of the business’s data resources and know when, how, and which to use

BASIC QUALIFICATIONS

• BS degree in Accounting, Business, Data Science, Economics, Finance, Mathematics, or a related field or equivalent experience
• Experience with data investigation across business processes/business systems, especially SQL proficiency pulling data from various sources.
• Demonstrated strength in SQL, data modeling, ETL development, and data warehousing
• Multiple years of experience in data engineering or analytics within a technology environment
• Advanced skills in Excel as well as any data visualisation tools like Tableau or similar BI tools
• Advanced ability to draw insights from data and clearly communicate them to the stakeholders and senior management as required
• proficiency with Alteryx
• Strong organisational and multitasking skills with ability to balance multiple priorities

PREFERRED QUALIFICATIONS

• Experience within Tax/ Accounting
• Familiarity with API’s, Javascript, python
• Knowledge of data management and modeling fundamentals and data storage principles
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience building large scale data products incrementally and integrating and managing datasets from multiple sources