Position Description:

Develops core digital analytics capabilities and enhances the usage of digital data across the organization. Enhances the digital analytics and digital Voice of Customer capabilities across all platforms. Identifies lagging business processes and develops improvements for these processes. Provides technical guidance and expertise to business partners to increase their understanding and utilization of platform capabilities and technologies. Designs and builds web and mobile based architectures to implement privacy and content modules. Conducts code reviews and evaluates code branching and delivery strategies. Enhances and customizes tools for marketing, tag management, quantitative data generation, qualitative data capture and VoC functions. Develops custom dashboards and identifies friction points. Provides guidance to stakeholders post-implementation to ensure solutions are fully utilized.

Primary Responsibilities:

• Uses custom tools to implement marketing technology tags supporting qualitative and quantitative data analytics for web and mobile platforms.
• Works closely with developers, engineers, and data analysts to identify business and system requirements, maintain data bases, implement quality control measures, and execute automation initiatives.
• Develops tag specification documents and tag implementation strategies based on business requirement in consultation with internal stakeholders.
• Collaborates with data analysts to maintain clean data in enterprise data lake tools like Snowflake.
• Provides assistance to quality assurance team and conducts quality checks on code.
• Reports on key metrics, analyzes and interprets trends, and provides actionable insights based on available analytics data.
• Collaborates with site developers to modify the data layer to improve analytics.
• Performs debugging using debugging tool Charles Proxy.
• Provides technical training and coaching to junior team members.
• Works with the team to foster innovation and learning initiatives.

Education and Experience:

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and  five (5) years of experience as a Principal Software Engineer/Developer (or closely related occupation) analyzing large scale datasets (containing 150M+ records) and providing actionable insights to improve digital marketing strategies using tag management systems and data visualization tools in a financial services environment.

Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Principal Software Engineer/Developer (or closely related occupation) analyzing large scale datasets (containing 150M+ records) and providing actionable insights to improve digital marketing strategies using tag management systems and data visualization tools in a financial services environment.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) setting-up, tracking, and collecting user feedback, and interpreting digital marketing campaigns, website traffic and user behavior utilizing platforms including Ensighten, Google Tag Manager, Adobe Dynamic Tag Manager, Adobe Launch, and Qualtrics.
• DE analyzing large scale datasets (containing 150M+ records) and performing segmentation and analysis, including A/B testing, funnel analysis, cohort analysis, and attribution modeling, to derive insights using Adobe Target, Adobe Sitecatalyst, Contentsquare, and Tableau.
• DE analyzing datasets and providing actionable insights to improve digital marketing strategies using both tag management systems including Ensighten or Google Tag Manager, and data visualization tools including Adobe Sitecatalyst, Tableau, and Qlik Sense; and tracking implementation, troubleshooting, and manipulating data using HTML, CSS, JavaScript, JQuery, Python, and R.
• DE querying, merging, and analyzing transactional data to create actionable schema structures for analyzing and identifying prescriptive analytical insights using SQL in Hadoop or Snowflake.

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