Job Description
About the position
- Responsibilities
- Driving the run-and-operate transformation initiative and delivering an in-depth analysis of Verizon's revenue, profitability, products, services, promotion, pricing, and customer trends to guide business decisions.
- See beyond what is requested and build solutions that address the current and anticipated data needs of the business.
- Quickly interpret complex business requests and break them down into smaller problems in terms of complexity.
- Evaluate and offer feedback on reports and data visualizations.
- Examine visual reports for insights or anomalies by various dimensions.
- Leading and executing the automation of reporting solutions using Qlik, ThoughtSpot, Looker, Knime, Alteryx, Google Workspace apps, Gemini, Teradata and BigQuery.
- Establish best practices for building reports, dashboards, pinboards, and other visualizations.
- Share the best practices to democratize reports and dashboard development but with safety guard rails.
- Understand how business units use visualization tools and build a framework for business units to create visualizations using a single source of truth.
- Develop guidelines on which visualization tool to use in what scenario to enable simplicity and efficiency at scale.
- Provide requirements to the data products team.
- Translate cross-functional business requirements into data product requirements to enable multiple uses for each data product.
- Understand the evolution of industry trends and techniques to envision easy-to-use business intelligence solutions.
- Participate in cross-functional project teams to identify critical items required from a reporting perspective.
- Continue identifying opportunities to enhance data analysis, reporting efficiency, and methodology.
- Stay on top of business changes, identify new gaps in data, and keep production reports and dashboards 'relevant' to the business at all times.
- Collaborate with teams to establish clear goals and KPIs, assist in delegating tasks and setting project deadlines.
- Contribute to creating a positive and motivating work environment and atmosphere for success.
- Offer coaching and mentoring to provide guidance on implementing solutions and assist other team members in resolving any issues or conflicts.
- Requirements
- Bachelor's degree or four or more years of work experience.
- Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
- Two or more years of experience in Teradata.
- One or more years of experience developing datasets on Qlik or ThoughtSpot platforms.
- Experience in successfully driving large-scale adoption of self-service analytics platforms.
- One or more years of experience supporting Analytics for Finance teams.
- Experience managing a small team.
- Knowledge and experience in Knime, Alteryx, Python, Gemini, Google Apps Script, and BigQuery.
- Nice-to-haves
- Bachelor's or Master's degree in Finance or any data discipline.
- Expert understanding of Business Intelligence and associated disciplines.
- Understanding of all facets of data, including data engineering, data products, analysis, visualization, predictive analytics, and prescriptive analytics.
- Excellent analytical skills and problem-solving experience, with the ability to break down a problem into its components and solve it using subjective and objective techniques.
- Experience working in a modern Data Warehouse using current technologies and services.
- Demonstrate advanced knowledge and understanding of Telecommunication data sets - Wireline, Wireless & Network data set.
- Outstanding communication, presentation, and interpersonal skills.
- Ability to inspire other team members with energy and passion to achieve transformational change with new working methods.
- Proven experience driving change to achieve results in smaller intervals while aiming for the North Star transformation goal.
- Proactive problem-solving capabilities.
- Knowledge of advanced technology concepts like Teradata, Big Query, Big Data, Hadoop, Hive, Cloud, etc.
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