Senior Data Engineer @

1 day ago


Remote Kraków, Czech Republic AVENGA Full time
  • Solid experience in Airflow, Python programming and SQL.
  • Knowledge of AWS services and kubernetes.
  • Bachelors in Mathematics, Computer Science or other relevant quantitative fields
  • Strong analytical and quantitative approach to problems
  • Knowledge of Data Engineering best practices in Data Quality, Observability, etc
  • Comfortable in dynamic and changing environment
  • Strong inclination to take responsibility for your work
  • Eagerness and hunger to learn - on the job learning
  • Excellent communication and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders 

Our client is a fintech company that provides banking and financial services. Their activities are connected with savings and investments.
The company collaborates with about 400 banks and financial institutions from more than 30 countries.
The company's online banking system allows customers to deposit at partner banks across Europe. 
The company's purpose is to provide savers with the best interest rates. The customer should only transfer the funds to their free Raisin Account and then open and manage their deposits. They can choose a bank with better interest rates. 

,[Deliver and manage the data warehousing aspects of business intelligence and Analytics. This includes the capability to architect, design, develop and support data extraction, transformation and orchestration processes in addition to data modelling and performance optimization on the data warehouse., Create and optimize data pipelines using Airflow, Snowflake and AWS., Work with the analytics team to design and develop the BI tool semantic layer from an engineering perspective (modelling, performance optimization etc...), Mentor junior individuals and help them develop their skills as required. , Plan, Delegate, and regulate workload within the team., Work with other teams in the organization (upstream application tech teams and Stakeholders) to plan the roadmap for the data organization and execute accordingly., Execute proofs of concept to test and evaluate new tools and technologies relevant to business intelligence and analytics and propose adoption wherever necessary., Connecting to OKRs, offering support in managing the OKR lifecycle, running macro planning sessions and macro retrospectives for continuous improvement. ] Requirements: Airflow, Python, SQL, AWS, Kubernetes, Data engineering, Data warehouse, Data pipelines, Snowflake, BI, Data modeling, Tableau, dbt, Analytics platform, Looker Additionally: Free coffee, Bike parking, Playroom, Shower, Free snacks, Free beverages, No dress code.

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