Senior AWS Data Engineer

Hello, let’s meet!

We are Xebia a place where experts grow. For nearly two decades now, weve been developing digital solutions for clients from many industries and places across the globe. Among the brands we’ve worked with are UPS, McLaren, Aviva, Deloitte, and many, many more.

Were passionate about Cloudbased solutions. So much so, that we have a partnership with three of the largest Cloud providers in the business – Amazon Web Services (AWS), Microsoft Azure & Google Cloud Platform (GCP). We even became the first AWS Premier Consulting Partner in Poland.

Formerly we were known as PGS Software. In 2021, we joined Xebia Group – a family of interlinked companies driven by the desire to make a difference in the world of technology.

Xebia stands for innovation, talented team members, and technological excellence. Xebia means worldwide recognition, and thought leadership. This regularly provides us with the opportunity to work on global, innovative projects.

Our mission can be captured in one word: Authority. We want to be recognized as the authority in our field of expertise.

What makes us stand out? Its the little details, like our attitude, dedication to knowledge, and the belief in peoples potential emphasizing every team members development. Obviously, these things are not easy to present on paper – so make sure to visit us to see it with your own eyes!

Now, weve talked a lot about ourselves – but wed love to hear more about you.

Send us your resume to start the conversation and join the #Xebia.

You will be:

• responsible for atscale infrastructure design, build and deployment with a focus on distributed systems,

• building and maintaining architecture patterns for data processing, workflow definitions, and system to system integrations using Big Data and Cloud technologies,

• evaluating and translating technical design to workable technical solutionscode and technical specifications at par with industry standards

• driving creation of reusable artifacts,

• establishing scalable, efficient, automated processes for data analysis, data model development, validation, and implementation,

• working closely with analystsdata scientists to understand impact to the downstream data models,

• writing efficient and wellorganized software to ship products in an iterative, continual release environment,

• contributing and promoting good software engineering practices across the team,

• communicating clearly and effectively to technical and nontechnical audiences,

• defining data retention policies,

• monitoring performance and advising any necessary infrastructure changes.