
Digital Marketing Analytics Professional
4 days ago
Lead Data Analyst Job Summary
\The role of a Lead Data Analyst involves working with strong analytical skills and experience in handling digital marketing data.
\This position requires navigating various platforms, including web analytics, ad platforms, and other allied data sources, to turn insights into meaningful results for business stakeholders.
\This is a hybrid Digital/Marketing Analytics role that goes beyond the scope of a purely 'web analyst' or strictly 'data analyst' position. The key characteristics of this role are:
\- Multidisciplinary Focus: The role demands expertise across multiple digital platforms, such as GA4 (or equivalent), and other MarTech/AdTech data sources like CRM, ads, and surveys.
- Expanded Data Landscape: Proficiency in SQL and BigQuery indicates a focus on large-scale data processing and integrating data from various sources, setting it apart from general data analysts who may not specialize in marketing performance metrics or digital marketing platforms.
- Marketing & Performance Insights: Translating data into actionable insights to optimize campaigns and improve ROI indicates a marketing analytics tilt, requiring an understanding of marketing funnels, conversions, and campaign KPIs.
Key Responsibilities
\- Digital Marketing Analytics: Experience with web analytics tools (GA4, Adobe Analytics, etc.) and familiarity with common marketing channels (paid ads, SEO, email) and how their data is tracked.
- SQL & Data Querying: Proficiency in extracting and manipulating data using SQL (BigQuery or similar databases) with ability to optimize queries and handle mid-to-large datasets.
- Multi-Source Data Wrangling: Comfortable cleaning, merging, and normalizing data from different platforms (CRM, ad platforms, surveys) and addressing outliers and inconsistencies in datasets.
- Data Visualization & Reporting: Skilled in creating dashboards and reports with Looker Studio, Tableau, Power BI, or equivalent tools and able to present complex data in a clear, actionable format.
- Basic Statistical Methods: Understanding of fundamental statistics (e.g., hypothesis testing, regression basics) and capable of running A/B tests and validating data findings.
- Marketing Performance Metrics: Knowledge of KPIs such as CTR, CPA, ROI, LTV, etc., and ability to connect these metrics back to broader business objectives.
- Communication & Stakeholder Management: Excellent at translating data insights into non-technical language and experience working cross-functionally with product, marketing, or data engineering teams.
- Critical Thinking & Problem-Solving: Strong analytical mindset to spot trends and derive strategic recommendations, creative in finding data-driven solutions to marketing challenges.
- Adaptability & Continuous Learning: Willingness to explore new analytical tools and stay updated with MarTech/AdTech trends and eager to learn and leverage evolving data methodologies to drive better results.
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