Data Analyst

Top Skills Required:

1. Data Validation and Quality Assurance:

• Proficiency in deep data analysis using tools such as Power Pivot, Adobe Analytics, Business Objects, and Tableau.
• Experience with enterprise-scale web analytics implementations, report creation, and diagnosing analytics instrumentation problems.
• Ability to identify and investigate data issues across platforms and applications.
• Skilled in assessing releases and hot fixes to make informed Go/No-Go decisions.
• Experience in defect management using tools like TDP, JIRA, iTrack, and AgileCraft.
• Ability to evaluate, document, and improve data test cases with development and QA colleagues.

2. Hands-on Experience with Debugging Tools:

• Experience with browser development tools, including console, network, and sources tabs.
• Familiarity with web redirect/rewrite rules and traffic analysis using tools like Charles, Fiddler, and Requestly.
• Experience with test automation, such as Selenium, and recorded web sessions in Tealeaf and Quantum Metrics.
• Proficiency in debugging traffic from native/mobile apps on emulators and physical devices.
• Experience extracting and cross-referencing data from warehouses using SQL and other internal tools.
• Knowledge of writing data specifications and data design documentation.

3. Technical Comprehension, Design, and Project Management:

• Understanding of web-related concepts such as A/B testing, personalization, segmentation, and targeting.
• Ability to collaborate with multiple disciplines, including product managers, business owners, reporting partners, analytics product team, and database administrators.
• Good understanding of client-server architecture for web experiences and native apps.
• Strong familiarity with product management and agile development processes; proactive communication skills desired.
• Ability to learn, adhere to, and promote data governance standards.
• Proficient in weighing and comparing cost vs. benefit in solution design decisions based on reporting requirements.
• Ability to understand complex data structures and user contexts across disparate applications and technologies.
• Proficiency in navigating the interplay between various technologies and data formats, such as APIs, SDKs, Kafka, JavaScript, HTML, JSON, XML, etc.