Senior Data Engineer

  • Full time
  • Prague
  • Posted 2 months ago
Helm (advanced)
Kubernetes (advanced)
Terraform (advanced)
Azure (advanced)
Python (advanced)
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About the project: 

The project is about creating two microservices:
  1. Stock Position 
  2. Stock Mutation for physical grocery stores in the Netherlands. 
Stocks are the heart of a store and currently they are in an Oracle monolith.
The stock information of the stores will be consumed by IT sub systems like Data Lake, Finance, Store Operations, Sustainability, Replenishment systems, End Consumer Mobile applications. 

The project has to ensure that this information is available in a performant way via API’s and will act as a golden source.

Tech Stack: 
  1. Data Engineering: Pyspark, Python, Azure SQL, Azure Synapse, Azure Data Factory, Azure Data Lake, Spark SQL, Databricks
  2. Platform Engineering: Azure Devops, Terraform, Databrics, AWX Ansible, Kafka, Mule
  3. Infrastructure: Azure, Terraform, Kubernetes (AKS), Helm, Docker

  • 5+ years of experience designing and implementing data platform solutions that processed, transformed data efficiently, secure and reliable.
  • Strong programming skills in Python.
  • Strong hands-on Azure data technologies experience such as ADLS, Databricks, EventHub, Synapse, SQLServer, DevOps, Terraform, Python, PySpark Bash, Git.
  • Agile and DevOps mindset and experience in architect role in such environment
  • A deep understanding of software development
  • Solution oriented and result driven
  • Excellent verbal and written communication skills , able to communicate with business and translate requirements into concrete user stories, work with a team to refine and realize stories.
  • Strong ability to design, document, present, communicate and implement a solution. 
  • Strong interpersonal skills and ability to deal with complexity of large organizations
  • Good knowledge of English (min. B2 level)


  • Building quality software and infrastructure (Azure based Data Platform)
  • Development of data models and processing of raw data at scale to make it available for analysis
  • Desiging, building and maintaining data pipelines to ensure highly accurate and reliable solutions for analytical needs
  • Analyze and improve efficiency, scalability, and stability of applications
  • Identify unnecessary complexity and remove it
  • Understanding business context and translate stakeholder needs into well-designed data models
  • Work cross-functionally with analysts and various engineering and data science teams to identify and execute new opportunities 
  • Create structured and reliable documentation;
More about Stepwise: 
  • Juicy tech stack: 
  • A great work environment with passionate and skilled people
  • No procedures and other corporate “beauties”
  • A flat organization with no levels of middle management between staff 
  • Possibility of choosing tools, languages & libraries
  • International projects from France, Germany, Netherlands and UK 
  • We know what is Work-Life Balance by example
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Still not convinced?
We invite you to our office. See how we work and talk to the team. 

To apply for this job please visit