Business Intelligence Engineer, MENA CX Product
4 weeks ago
Job ID: 2934084 | Q-Express Documents Transport
Our team owns building products for the onsite shopping CX of MENA customers. We are looking for a Business Analyst to lead the efforts to quantify the customer funnel, build entitlements, and automate the daily/weekly tracking of shopping events. The leader in this role is the starting point of product roadmap creation, needs to demonstrate customer advocacy and develop a strong hold on quantified customer behavior. This role partners with Product managers, Tech and Business teams in MENA, and WW to establish feature value. It is placed in a fast-paced ambiguous space, which will require the candidate to work with speed, and depth all together. They will need to influence stakeholders, and lead communication with L8+ leaders.
Key job responsibilitiesThis role owns shopping funnel entitlements and enables features to be quantified to establish their contribution to closing entitlement gaps. MENA is a dual language region and the role owns reporting of shopping journeys in both languages for regular stakeholder reviews. The candidate will dive deep into platform impact of launched/in experiment features and lead course correction with Product Managers. Data sources for customer events are not standardized and this role also innovates for securing access to the right customer event data to establish impact.
BASIC QUALIFICATIONS- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- 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
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