Senior Data Designer
- Belgrad
- Charków
- Dnipro
- Erywań
- Kijów
- Kluż-Napoka
- Kraków
- Larnaka
- Łódź
- Lublin
- Lwów
- Odesa
- Remote.Bulgaria
- Remote.Georgia
- Remote.Poland
- Ryga
- Sofia
- Tbilisi
- Warna
- Warszawa
- Wrocław
Jeśli otrzymałeś tę ofertę pracy od naszych rekruterów, zapoznaj się z naszą Polityką prywatności.
Position overview
The role involves occasional business trips to the office in Krakow, typically once a month or once a quarter, depending on team needs.
Responsibilities
- Gather and analyze business requirements related to data warehousing.
- Act as the main point of contact between business stakeholders and the development team.
- Translate business requirements into clear data models, mappings, and functional documentation for Data Engineers.
- Design and document data ingestion flows from existing and new data sources.
- Collaborate with the Principal Data Designer on solution design and data modeling decisions.
- Ensure designs meet business needs, follow data design principles, and are delivered accurately and on time.
- Maintain and improve documentation standards, templates, and design processes.
- Review colleagues’ designs and provide constructive feedback.
- Support cross-team collaboration and help other workstreams when needed.
Requirements
- Strong experience in data modeling for enterprise Data Warehouses.
- Good understanding of data warehousing concepts, data structures, and source-to-target mappings.
- Experience working as a bridge between business stakeholders and technical teams.
- Strong analytical skills with the ability to translate business needs into clear technical documentation.
- Experience preparing functional specifications, mappings, and design documents for development teams.
- Ability to work collaboratively in an Agile environment.
- Strong communication skills and confidence when working with stakeholders across different teams.
- High attention to detail and strong ownership of deliverables.
- Ability to challenge decisions constructively and contribute to design improvements.
- Proactive approach to learning and continuous improvement.
Nice to have
- Querying and transforming data using SQL, Python / PySpark.
- Conducting detailed data profiling and analysis.
- Modelling data into a complex facts and dimensions, identifying suitable mappings, aggregations and snapshot tables where appropriate.
- Identifying complex data quality rules, considering alternative sources and volumetric analysis.
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Zgodnie z oficjalnym kalendarzem, niezależnie od kalendarza klienta
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