Consumer Analytics (CA)
is responsible to deliver analytical products to adidas’ Digital organization. These products may include reports, dashboards, data models, data pipelines as well as data science and machine learning algorithms.
address mostly adidas-internal audience (e.g. digital analysts, management, other operational teams) but not only – some of them also build the foundation for consumer facing products like digital communications or web-site & app personalization. While our full delivery capacity is assigned to the Digital organization, we technically sit within a different part of the organization, the Data & Analytics (DNA) department.
We are an internal team of around 30 professionals with lots of experience on data engineering, project management and solution architecture and span across three different geographies, Herzogenaurach/Germany, Gurugram/India and Zaragoza/Spain. Beyond our internal team, we are scaling our delivery through external vendors, too.
Join our team of Data Engineers in our Headquarter in Herzogenaurach and become a crucial part in creating the future through the development of a game-changing analytical infrastructure.Key Responsibilities:
You will be part of a highly engaged, multinational agile team, in charge of creating and enhancing digital data products, reporting directly to the Team Lead Data Engineering in Herzogenaurach. You will be showcasing your creativity by using latest big data technology trends to bring ideas to life.
To embrace this challenge as a Big Data Engineer, you will need to:
Requisite Education and Experience:
- Develop Big Data pipelines using Apache Spark in the AWS environment.
- Code in Python and/or Scala.
- Deal with SQL and analytical data base systems like Exasol.
- Automate processes by implementing CI/CD in Jenkins.
- Have the passion and ability to write clean, readable, well-designed and well-documented code along with tests.
What we are looking for:
- Bachelor’s degree equivalent in Computer Science, Information Technology or similar field of study, Master is a plus.
- At least 5 years experience in data engineering, ideally in an agile environment (e.g. Scrum).
- Passion for data, technology, digital and sports.
- Strong interpersonal and communication skills, strong hands-on mentality.
- Fluent in English.
- Someone passionate about working with data.
- SQL and passion for proper engineering is essential.
- Good, general understanding of data warehousing and data modelling.
- Proven working experience with Big Data technologies, esp. Spark.
- Track record of developing true Big Data pipelines in Python/PySpark and/or Scala
- Experience with AWS environment, esp. EMR and S3
- Scala, Spark, Hadoop, Hive
- AWS, S3
- SQL (Exasol) and ETL (Alteryx)