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Nike DIR, GC ANALYTICS ENGINEERING - GOAL - Shanghai in Shanghai, China


What You Bring

• Bachelor/master degree in Computer Science or related technical subject area or equivalent combination of education and experience.

• 12+ years of validated experience in software engineering, data engineering, or related field preferable in Supply chain data

• Experience building effective engineering teams and leading organizational and cultural change

• Strong problem solving and analytical mindset with a strong product and a customer-first mindset

• Experience establishing Engineering processes and best practices

• Familiarity with cloud architecture and technologies, in particular, AWS

• Familiarity with data engineering technologies, in particular, Sparks, Kafka and Databricks

• Familiarity with agile development and test-driven development

• Understanding of data modeling and software architecture

• Effective communication skills

• Expertise in relational SQL

• Expertise designing, estimating and implementing for complex software projects involving RDBMS systems, SQL and SQL Analytical functions. Strong programming experience, Python or Scala preferred.

• Expertise in scripting languages such as Shell, Python

• Ability to identify and solve issues concerning data management and data quality

• Strong understanding of data structures, algorithms, and data solutions

• Working experience in building cloud, scalable, real-time, and high-performance data lake solutions, preferably using AWS stack, would be an advantage

• Expertise in agile development and test-driven development

• Experience with data warehouse tools like Snowflake.

• Good understanding of principles of solution architecture and technical design

• Solid Experience with messaging/streaming/complex event processing tooling and frameworks such as Kinesis, Kafka, Spark Streaming, Flink, Nifi, etc.

• Solid Experience working with NoSQL data stores such as HBase, DynamoDB, etc.

• Solid Experience building RESTful API’s to enable data consumption.

• Knowledge of Nike Technology landscape including Dimensional data at Nike.

• Proven ability to quickly pick up new languages, technologies, and frameworks.

• Experience participating in key business, architectural and technical decisions, providing guidance and mentorship to other engineers.

• Experience in Agile/Scrum application development.

The following skills and experience are also relevant to our overall environment, and nice to have:

• experience with performance and scalability tuning (Understanding of Teradata capabilities and how to optimize design for performance within Teradata architecture.)

• Experience with build tools such as Terraform or CloudFormation and automation tools such as Jenkins or Circle CI.

Who Are We Looking For

We are looking for director analytics engineering on the GC Enterprise Analytics Engineering team. You will work with a variety of hardworking Nike teammates and be a driving force for building world-class solutions for Nike Technology and its business partners, working on development projects related to Analytics, Supply Chain, Commerce and Consumer behavior among others. Your strong problem-solving and interpersonal communication skills, desire to learn and share knowledge with others will position you well for this role.

What Will You Work On

you will manage and coordinate all the data engineering work GC Supply chain data products. Data is the life blood of Nike's Direct to consumer strategy!

You will develop and implement the data analytics engineering strategy with your peers to enable global Nike goals. In addition, you will challenge your teams to evolve their engineering practices and processes, pioneering new techniques to push the limits of productivity within the organization, collaborating with the product organization to ensure that your teams work on the most valuable data products used all across the company. Finally, you will mentor and elevate your teammates and help them get to the next stage of their careers. Being, at the same time, a core of the talent strategy, helping Nike find and retain top talent.

You thrive when surrounded by skilled colleagues and aim never to stop learning. We are looking for leaders who enjoy a collaborative and fast-paced environment where we develop and share new skills, mentor, and contribute knowledge and software back to the analytics and engineering communities both within Nike and at large. We value and nurture our culture by always looking to be collaborative, intellectually curious, fun, open, and diverse.

Who will you work with

In this role, you'll be working closely with the rest of our cross domains Data Engineering team, along with Product and Customer Success teams. This role reports to the SD of Enterprise Data Engineering in the GC Enterprise Data and Analytics Organization.

Role responsibilities:

• Lead the engineering team to design and implement data products and features in collaboration with product owners, data analysts, and business partners using Agile / Scrum methodology.

• Contribute to overall architecture, frameworks and patterns for processing, evaluate and apply new technologies/tools/frameworks centered around high-volume data processing.

• Use continuous integration and deployment frameworks including automated unit tests and integration testing.

• Define and apply appropriate data acquisition and consumption strategies for given technical scenarios, build utilities, user defined. functions, libraries, and frameworks to better enable data flow patterns.

• Engineering Delivery.

• Design and implement remediation data workflows and script prevalent in the Nike data ecosystem including automated routines using workflow orchestration tools.

• Drive the development of new data products and the optimization of existing solutions.

• Provide work estimates and represent work progress and challenges..

• Profile and analyze data for the purpose of designing scalable solutions

• Anticipate, identify and solve issues concerning data management to improve data quality, address operational & performance issues, remove technical bottlenecks and perform root cause analysis as needed.

• Team Leadership and Collaboration.

• Drive collaborative reviews of designs, code, and test plans.

• Work with architecture, other engineering leads and teams to ensure quality solutions are implemented, and team adheres to defined engineering standard methodologies.

• Provide leadership, guidance and mentorship to other data engineers.

NIKE, Inc. is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, protected veteran status, or disability. NIKE is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the employment process, please call +1 503-671-4156 and let us know the nature of your request, your location and your contact information.