Software Engineer II, ITC
INDIA TECHNOLOGY CENTER
Nike
Inspiration und Support für alle Athlet:innen mit innovativen Produkten, Experiences und Services. Spare 25 % am Nike Black Friday. Es gelten Ausnahmen.WHO YOU’LL WORK WITH
This role is part of the Nike’s Customer Data Platform within Marketing Technology. This team works on a variety of data points across Geos from Nike’ experiences, Data Science Models, Transaction Data, Permissions etc. which are stitched together to create a rich customer overview that provides the marketers a buffet of options to choose for a marketing activity or build a insight. This team is powered by Data Engineering, Customer Data platform software service and many home-grown tools based on cutting edge technologies.
WHO WE ARE LOOKING FOR
We are looking for a Software engineer, to be a part of Nike’s Marketing Technology organization. This position will play a critical role, in developing Nike’s Customer Data platform, which supports and promotes our products and provides a unique user experience to all our customers in166 countries globally. We are looking for someone to have a strong Data engineering and analytical background with a focus of delivering an omnichannel consumer experience through data driven marketing.
We are looking for a candidate with a strong 2-5 years of experience on working on large datasets and should demonstrate below skills:
Academic background in computer science (BE or B Tech) or equivalent work
2-5 years of technology related experience
Hands-on experience in data engineering developing batch and streaming pipeline
Hands on experience on Python or Java, SQL, Data Engineering, experience with the following tools or similar: Data Bricks Airflow, EMR, Hive, Spark
Demonstrated strength in data modelling, ETL development, and data streaming
Experience in microservices architecture, domain driven design, and RESTful API’s
Knowledge of data management fundamentals and data storage principles
Experience in customizing product solutions
Familiarity with the challenge of moving large files across a geographically disperse network. Knowledge of different accelerated transfer methods and technologies
Experience with implementing CI/CD and leading teams with DevOps responsibilities of deploying and supporting the software in production
Experience using cloud services to build an integrated application in production (AWS - EC2, ECS, API gateway, Lambda).
Experience with implementing CI/CD and DevOps responsibilities of deploying and supporting the software in production
Marketing technology experience is a plus
Experience integrating with various Adobe toolset in the marketing space would be a plus– in particular Adobe Experience Platform (AEP), Journey Orchestration (JO), Customer Journey Analytics(CJA)
WHAT YOU’LL WORK ON
This role will be responsible for driving, owning, and shipping all aspects of large, multi-functional efforts feature areas and will partner with engineering teams throughout feature development from architecture, design, implementation, and validation.
Design, and build large datasets, and data pipelines to support building out our new Customer Data Platform (CDP) which will enable advanced segmentation in Customer data platform, that creates unique customer experience targeting, automation, and analytics.
Build complex data pipelines for real time data, click stream analysis and work to achieve high-quality data ingestion goals.
The technology stack that you will be working on: Data Bricks, Python, AirFlow, AWS, EMR, Databricks.
Innovating, architecting, designing, and implementing highly available, scalable systems, focusing on highly visible marketing initiatives
Contributing ideas for new features and identifying technical areas for improvement proactively
Collaborate with upstream and downstream technical teams to develop integrations to provide a seamless flow of our marketing assets from planning to delivery.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow APIs Architecture AWS CI/CD Computer Science CX Databricks Data management Data pipelines DevOps EC2 ECS Engineering ETL Java Lambda Microservices Pipelines Python Spark SQL Streaming
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