DATA Engineer
Tech Stack
Job Description
🔵 PAYBACK is the world’s leading multi-partner loyalty program.
As an international player, we operate in German, Italian, Mexican, and Austrian markets.
More than 10 million active customers already use the German PAYBACK app and mobile PAYBACK services via their smartphones.PAYBACK is a top player in data-driven marketing.
With the ability to develop digital business models and implement technical trends, we are one of the leading companies in the data economy.All technical solutions of the PAYBACK program are developed, invented and implemented in Germany.
Therefore, we provide the latest technologies and have cross-functional and agile teams.You want to take responsibility and collaborate your ideas to our unique product?
You are ambitious and eager to and move things further?
Then you are exactly right with PAYBACK.We are looking forward to getting to know you.TECHSTACK: Git, Python, Airflow, SQL, NoSQL, Spark, MapR, Google Cloud Services (BigQuery, Cloud Build, Cloud Storage, Pub/Sub, Cloud Composer, DataFlow).Description: Within the Global DWH Engineering Team you can work with a huge amount of data and help us to improve by using it in the right way in Germany, Poland, Mexico, Italy and Austria.We’re not only dealing with data, but also heading towards Continuous Integration and Continuous Delivery and constantly improve and converge our systems to become a truly Global Data Warehouse by migrating our services into the public cloud.You will be responsible for development, automation and the maintain of our services on-premises and within the cloud.Your responsibilities:Within the Data Engineering Team you can work with a huge amount of data and help us with its usage in an efficient way in Germany, Poland, Mexico, Italy and Austria.We strive towards a modern cloud-based data platform on GCP leveraging bleeding edge services and in parallel we keep existing processes running on-premise until they are fully migrated.You will not only be responsible for development but also for the operation of our services, both on-premise and within the cloud.You support operations and take responsibility of productive processes (you build it, you run it).You analyze, understand, and accompany the requirements from the idea until end-of-life (DataOps)You contribute to the design of our solution, execute development of design, test and document your implementation.In order to solve complex business problems, you perform comprehensive data analysis and research.You work together with internal stakeholders across the organization to produce high-quality KPIs out of raw data.You work in close collaboration within your cross-functional agile team on-side.Your Profile:You have 4+ years of work experience as a Data Engineer with huge datasets or in a similar position.You are a clean coder with an agile mindset.Mass data doesn't scare you.You have experienced with/you are eager to learn Kubernetes/OpenShift, data related GCP services or MapR Cluster.You are characterized by a high-quality awareness, your trustworthiness and interest in new technologies.You can work independently in an agile team.You have very good English skills.How about?
Employment contract?
📝Of course.
With us you do not have to worry about stable employment.Great location 🏬 Still like!
We invite you to our new office at Rondo Daszyńskiego metro station.
Currently we also work from home.Flexible working hours?
⏰Sounds great!
We start working between 8 to 10.Working in a hybrid model?
💻Of course!
You work with us 2 days a week from the office, 3 days a week from homeFriendly atmosphere at work?
🤝🏻Yes!
In PAYBACK, people are the most important asset.Work wherever you want?
🌴In PAYBACK you have the opportunity.
Working 100% remotely, also from European countries for 10 days a year.Dress code?
👕We definitely say no.
There are no rigid dress code rules in our company, sneakers are more than welcome.Trainings?
🧠Of course.
We provide training to develop hard and soft skills.Something is missing?
🖐Open communication is our priority, so dare to ask!