Lead Engineer Data & Analytics

Description

Job description
Nike is looking for a seasoned engineer who can lead and grow teams of data engineers and developers to support machine learning engineers and data scientists to deliver scalable machine learning and advanced analytics solutions to customers across our business. You will work on a variety of complex business problems such as forecasting, personalization, and inventory optimization. You will productionalize and scale solutions in the cloud as APIs, stream processing, or massive batch processing. You will leverage big data, parallel processing technologies, advanced analytics, machine learning, and deep learning techniques to quantitatively plan product demand, allocate resources, and target the right customers with the best products. You will foster partnerships with best of breed open source communities, commercial vendors, and universities. Above all, your work will accelerate Nike's core mission of serving Athletes. What youll do
Design and build reusable components, frameworks and libraries at scale to support analytics products Design and implement product features in collaboration with business and Technology stakeholders Identify and solve issues concerning data management to improve data quality Clean, prepare and optimize data for ingestion and consumption Collaborate on the implementation of new data management projects and restructure of the current data architecture Implement automated workflows and routines using workflow scheduling tools Build continuous integration, testdriven development and production deployment frameworks Collaboratively review design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards Analyze and profile data for the purpose of designing scalable solutions Troubleshoot data issues and perform root cause analysis to proactively resolve product and operational issues
Qualifications Experience building cloud scalable, real time and highperformance data lake solutions Strong experience with Python, Spark, Shell & SQL
Experience with AWS components and services, particularly IAM, ECS/EKS, EMR, S3, and Lambda/Serverless
Experience writing automation to deploy R (RStudio), Spark ML, and/or Python apps (pandas, numpy, scipy, keras, etc.)
Experience with Container Orchestration (Kubernetes, Docker,etc)
Experience with software engineering best practices including unit testing, continuous integration (Jenkins, CircleCI, etc), and source control (GitHub, Bitbucket,etc)
Experience with workflow scheduling tools like Airflow
Strong understanding of statistical modeling and machine learning techniques Experience building APIs and micro service architecture
Has a strong problem solving and analytical mindset
Proven successful trackrecord of learning new tools and technologies Able to influence and communicate effectively, both verbally and written, with team members
Nice to have Proficiency with data visualization tools and libraries like Tableau, Shiny, ggplot2
Retail Industry Experience
Experience with Snowflake