Senior Front-End Engineer – Marketing Analytics

Walmart Stores SAN BRUNO, CA

About the Job

Position Description


As a Front-End Data Engineer, you will help the World’s largest omni-channel retailer collect, organize and leverage robust data sets that will be used to manage and optimize the business. You will help define and expand upon our data pipeline, serving the needs of cross functional teams by providing best in class UI/UX design. The Data Engineer will ensure proper tagging and tracking is in place, and ensure the quality and consistency of data, making it available through UI tools to various teams including BI analysts, the campaign measurement team, data scientists, category marketers, and marketing channel owners.

Responsibilities:
•Provide UI/UX design and front-end web development that enables easy access and intuitive presentation of complex data.
•Analyze and recommend best in class front-end tools for various use cases.
•Create and maintain a robust data pipeline to support Marketing Vehicle performance, Category performance, Customer cohort activity, and Financial Plan/Forecast reporting.
•Lead the vision and secure support for a common data lake initiative, including defining use cases and capturing business requirements.
•Define taxonomy, data flow, and data formatting for various internal and external partners.
•Work with machine learning/data science team on implementation of data with AI models.
•Provide data architecture that is flexible, scalable, and consistent for cross-functional use, and aligned to stakeholder business requirements.
•Deliver the tools for ongoing and accurate reporting of KPIs for Weekly Business Review reporting.
•Publish KPI definitions and ensure they are consistent with Marketing Analytics, Marketing Finance, and Retail Operations expectations.
•Collect and be responsible for the accuracy of all data to be used in several ROAS models, including MM (Marketing Mix) and MTA (Multi Touch Attribution).
•Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
•Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using ‘big data’ technologies. Create data tools for BI and data science team members that assist them in accessing and leveraging all key data in real time.
•Provide analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics, including campaign and category performance, marketing vehicle performance, customer funnel metrics, and operational efficiency.
•Define SLA and acceptable time lags by data source, define QA process, and socialize resolution process to ensure data accuracy and consistency.

Minimum Qualifications


•4-6 years of experience in a Data Engineer role.
•BA/BS Degree in Computer Science, Statistics, Information Systems or another quantitative field.
-Software/Tools expertise:
-Experience with big data tools
-Experience with front end tools and languages, including Angular JS, Javascript, HTML, CSS, React JS, SQL.
-Experience with relational SQL and NoSQL databases
-Disciplined practitioner of the latest tagging and tracking techniques, including working knowledge of channel-specific challenges.
-Experience with data pipeline and workflow management tools
-Experience with various cloud services.
-Experience with object-oriented languages.
•Experience working across various internal stakeholders including Marketing, Finance, and Engineering. Strong skills in communicating technical material to range of audiences.
•Experience with organizing and presenting Customer Cohort data used in LTV analysis.
•Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
•Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
•Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
•Strong analytic skills related to working with unstructured datasets.
•Build processes supporting data transformation, data structures, metadata, and worklA successful history of building reporting and analysis tools that have been widely adopted within an organization to make key decisions.
•Strong project management and organizational skills.
•Experience supporting and working with cross-functional teams in a dynamic environment.

Additional Preferred Qualifications


•Masters or PhD in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
•Experience with full spectrum of Marketing channel data, including Mobile, Social, Email, SEM, SEO, Affiliates, and offline channels like TV and print.
•Strong analytical and quantitative skills and ability to translate findings into actions that align to the needs of the business.
•Strong organizational skills, with the ability to effectively manage projects, communicate effectively, and be a self-starter.
•Demonstrated thought leadership and relationship building/management with internal stakeholders and external partners.
•Experience with end-user focused data visualization tools such as Tableau, Thoughtspot, Looker and Domo.
•Omni-channel Retail experience.
•Experience and passion for working in a fast-paced agile environment.

Company Summary


The Walmart eCommerce team is rapidly innovating to evolve and define the future state of shopping. As the world’s largest retailer, we are on a mission to help people save money and live better.  With the help of some of the brightest minds in technology, merchandising, marketing, supply chain, talent and more, we are reimagining the intersection of digital and physical shopping to help achieve that mission.

Position Summary


As a Front-End Data Engineer, you will help the World’s largest omni-channel retailer collect, organize and leverage robust data sets that will be used to manage and optimize the business. You will help define and expand upon our data pipeline, serving the needs of cross functional teams by providing best in class UI/UX design. The Data Engineer will ensure proper tagging and tracking is in place, and ensure the quality and consistency of data, making it available through UI tools to various teams including BI analysts, the campaign measurement team, data scientists, category marketers, and marketing channel owners.

Responsibilities:
•Provide UI/UX design and front-end web development that enables easy access and intuitive presentation of complex data.
•Analyze and recommend best in class front-end tools for various use cases.
•Create and maintain a robust data pipeline to support Marketing Vehicle performance, Category performance, Customer cohort activity, and Financial Plan/Forecast reporting.
•Lead the vision and secure support for a common data lake initiative, including defining use cases and capturing business requirements.
•Define taxonomy, data flow, and data formatting for various internal and external partners.
•Work with machine learning/data science team on implementation of data with AI models.
•Provide data architecture that is flexible, scalable, and consistent for cross-functional use, and aligned to stakeholder business requirements.
•Deliver the tools for ongoing and accurate reporting of KPIs for Weekly Business Review reporting.
•Publish KPI definitions and ensure they are consistent with Marketing Analytics, Marketing Finance, and Retail Operations expectations.
•Collect and be responsible for the accuracy of all data to be used in several ROAS models, including MM (Marketing Mix) and MTA (Multi Touch Attribution).
•Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
•Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using ‘big data’ technologies. Create data tools for BI and data science team members that assist them in accessing and leveraging all key data in real time.
•Provide analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics, including campaign and category performance, marketing vehicle performance, customer funnel metrics, and operational efficiency.
•Define SLA and acceptable time lags by data source, define QA process, and socialize resolution process to ensure data accuracy and consistency.