big data platform engineer lead, Starbucks Technology - Seattle, WA - Full-time / Part-time

Are you a data engineer with a passion for highly scalable data and analytics solution that impacts millions of users ? Do you want to be part of a an awesome team lighting up terabytes of data everyday to power insights to help the organization make business decisions? Do you want to be a key part of a team setting the vision for the next generation analytics platform and executing on it?

This position contributes to Starbucks success by building data services for analytic solutions. You will build data pipelines that are scalable, repeatable, secure and adhere to data quality standards; provide end-to-end infrastructure design for our cloud tech and work collaboratively with IT, data science and the business to build batch/real-time data solutions. With a bias for action, you will leverage Agile to both fail fast and deploy MVP fast. You are primarily a data engineer but are passionate about developing engineering solutions to deploy data science algorithms that enhance customer experience and drive revenue for the business.

Models and acts in accordance with Starbucks guiding principles.

Summary of Key Responsibilities

Responsibilities and essential job functions include but are not limited to the following:

Leadership

• Lead discussions with other technical teams that are participating in solution delivery
• Lead discussions about technical alternatives and respectively champion their point-of-view
• Facilitates technical decision making by negotiating priorities, option and tradeoffs within the solution delivery team
• Assists team members and peers in learning technical skills and business acumen
• Provide recommendations to solution delivery team for resource allocations and actively participate in backlog grooming & iterative planning
• Coordinates prioritization of enhancements and backlog grooming

Solution Design

• Lead solution performance trade-off studies across all BI solutions
• Understand new business and technical requirements of the solution and how those requirements impact existing BI requirements
• Create, maintain and improve team coding standards
• Establish documentation standards for the team and review/approve documentation as necessary

Solution Delivery

• Create the technology vision for BI technologies and participate in applying the vision to business needs
• Lead the review of business capabilities to prioritize their inclusion into the business capabilities roadmap
• Lead the development of user stories from approved epics
• Demonstrate deep knowledge and ability to lead others to build and support highly available data, Batch and Real-time data pipeline and technology capabilities on Microsoft Azure.
• Support Data science/ Analytical workloads in data preparation, feature extraction by reshaping, wrangling and blending enterprise data sets and adhoc data sets into data assets that support exploratory data science. Validate data sets
• Perform the required data validation
• Operationalize Machine Learning models in Batch and Real Time Data Pipelines to create scalable analytical applications.
• Lead the resolution activities for complex data issues.

Site Reliability Engineering

• Evaluate proposed designs and design decisions to ensure reduced TCO
• Automate deployment of virtual resources
• Implement monitory and logging as part of solutions
• Define the appropriate KPIs that will provide insight into the operational heath of the solutions
• Lead by example by demonstrating the Starbucks mission and values.
• Work in an agile environment. Develop and drive multiple cross-departmental projects. Establish effective working relationships across disparate departments to deliver business results

Basic Qualifications

• Bachelor's degree in computer science, management information systems, or related discipline, or equivalent work experience
• Experience architecting and building big data pipelines using Spark, Map Reduce (3 years)
• Expertise in programming languages like Scala, Java, C# (3 years)
• Expertise in scripting languages like python, R (3 years)
• Experience in using Microsoft Azure for Data and Analytics solutions ( Azure Data Lake, Azure Data Factory, Azure Data Lake Analytics/ USQL, Azure Stream Analytics, Azure Machine Learning, Azure Storage ) (1 years)
• PowerShell, ARM (1 years desirable)
• Overall Data Engineering experience (6 years)

Preferred Qualification

• Ability to apply knowledge of multidisciplinary business principles and practices to achieve successful outcomes in cross-functional projects and activities
• Effective communication skills
• Excel at problem solving
• Proven ability and desire to mentor others in a team environment
• Practice, evangelize and be an ambassador for agile and DevOps culture
• Proven ability and desire to lead others in a team environment

Starbucks and its brands are an equal opportunity employer of all qualified individuals; including minorities, women, veterans, and individuals with disabilities, and regardless of sexual orientation or gender identity. Starbucks will consider for employment qualified applicants with criminal histories in a manner consistent with all federal, state, and local ordinances.