Senior 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.
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