We are seeking an experienced Analytics Data Engineer to join our Pizza Hut US team. This person will be responsible for taking ownership of existing data and analytics builds, automating new data and analytics jobs, and documenting processes in collaboration with, and in support of, teams that build data driven insights that contribute to Pizza Hut’s growth. While this role will operate in the background, this person will play a critical part in shaping our business strategy on key initiatives, ensuring we deliver the best pizza experience to our customers. The work environment is highly collaborative in a semi-agile setting with cross-functional teammates. The selected candidate will be assigned to the analytics team, but will work closely with data engineering to strictly follow best practices that team defines, especially for changes made to production tables and systems, and for transitioning analytics jobs over to the data engineering team's ownership.

Responsibilities

Support Data Analysis and Reporting:

• Support internal clients that analyze large datasets to extract meaningful insights and trends.
• Develop and maintain data and analytics processes that feed dashboards, reports, and visualizations that relay trends, results, and outcomes to stakeholders and senior leadership.
• Perform exploratory and investigative analysis to identify and quantify opportunities across various aspects of our business that can be measured with data.
• Be an expert on our data used for analytical purposes.
• Take ownership of existing automated processes and data products.
• Set up data feeds to 3rd party vendors and partners.

QA And Data Evolution

• Design and test processes prior to promoting to production.
• Troubleshoot and fix automation errors.
• Provide recommendations for column, or table design enhancements, or calculations, or attributes that would optimize analytics efficiency or improve data quality.
• Be creative and innovative in building solutions.

Cross-Functional Collaboration

• Work closely with cross-functional teams to understand business goals and objectives.
• Effectively influence, champion, and drive for results through prioritizing data cleansing and standardizing of production tables and views, assisting in the hand off of automated processes/data builds to the data engineering team, and setting up new automations to support the analytics team and dashboard development.
• Provide analytics support to various departments and assist in solving complex business challenges through set up/automation, and maintenance of, analytics processes.
• Identify processes that are good candidates to transition ownership to the data engineering team. Refactor or port over anything necessary to another type of platform or language to promote to the production environment owned by the data engineering team.

Data Management

• Ensure data quality and accuracy by collaborating with the data engineering team.
• Stay up-to-date with industry best practices and technologies related to analytics and data management.

Factors of Success

Required

• 6 years of experience in data engineering.
• 2 years of experience in data analytics.
• Proficiency in data engineering and governance languages and tools such as Airflow, SQL, and Alation.
• Proficiency in data analysis languages and tools such as SQL, Python, R, Alteryx, and dbt.
• Proficiency with code repositories and file version systems such as Git.
• Data visualization skills using tools like Tableau, Power BI, Domo, or similar.
• Written and verbal communication skills to convey complex findings to non-technical stakeholders.
• Strong problem-solving abilities and a results-oriented mindset.
• Stakeholder management and partnership capabilities.
• Visionary thinker, with the ability to see the bigger picture and ability to design data and systems for where the company should go.
• Proficiency in documentation, including:
  • Diagramming data processes and table relationships
  • Documenting within code
  • Creating and updating project documentation
  • Creating data dictionaries
  • And creating documentation for data and processes for the broader enterprise to leverage
• Ability to translate intricate details into understandable explanations.
• Technically astute, with a strong grounding in SQL and the conversion of business requirements to practical data and analytics design.
• Ability to think and work in terms of customer-level analytics.

Preferred

• QSR industry experience in data engineering and analytics
• Experience with data modeling

Salary Range: $­­112,200 to $132,000 annually bonus eligibility. This is the expected salary range for this position. Ultimately, in determining pay, we'll consider the successful candidate’s location, experience, and other job-related factors.