Data Engineer (DBX,dbt), Regular
⚲ Warszawa, Mokotów
Do uzgodnienia
Wymagania
- Python
- SQL
- PySpark
- dbt
- GitHub
Opis stanowiska
Nasze wymagania:
Strong experience with Databricks (DBX)
Advanced knowledge of Python (experience with libraries such as Pydantic is a plus; PydanticAI is a strong advantage)
Solid experience in building and optimizing ETL/ELT pipelines
Very good knowledge of SQL and relational databases
Experience with PySpark
Familiarity with dbt is a plus
Experience with Azure Data Services is an advantage
Knowledge of CI/CD practices and tools (e.g. GitHub)
General understanding of infrastructure, orchestration, and IT security principles
Proven experience in Data Engineering (Regular level)
Bachelor’s or Master’s degree in a technical field (e.g. Computer Science, Engineering) or equivalent experience
Fluent English (written and spoken)
DevOps mindset (“you build it, you run it”)
Ability to understand complex requirements and translate them into actionable solutions
Strong communication skills and ability to work with cross-functional teams
Attention to detail, especially regarding data quality and business logic
Proactive attitude, ownership, and willingness to learn new technologies
Experience in the insurance domain is a plus
Mile widziane:
Familiarity with dbt
Experience with Azure Data Services
Experience in the insurance domain
O projekcie:
We are looking for a Regular Data Engineer to join a new, innovative project for one of our key clients in the insurance industry. You will work in a hybrid model with teammates based in Poland and collaborate with global stakeholders, including direct interaction with business users. This project focuses on building an advanced solution leveraging Large Language Models (LLMs) to scan documents and support automated decision-making processes.
Zakres obowiązków:
Contribute by building a training dataset for document processing and decision support
Design and implement end-to-end data pipelines (ingestion, transformation, storage, and consumption)
Prepare and maintain high-quality training datasets for machine learning models
Work with large-scale data on a modern cloud data platform (Databricks)
Apply best practices in data engineering, testing, and deployment
Collaborate closely with data scientists, engineers, and business stakeholders
Continuously improve performance, reliability, and automation of data workflow
Oferujemy:
Contract under Polish law: B2B or Umowa o Pracę
Benefits such as private medical care, group insurance, Multisport card
There are English classes available
Hybrid work (at least 1 day/week on-site) in Warsaw (Mokotów)
Opportunity to work with excellent professionals
High standards of work and focus on the quality of code
New technologies in use
Continuously learning and growth
International team
Pinball, PlayStation & much more (on-site)
Strong experience with Databricks (DBX)
Advanced knowledge of Python (experience with libraries such as Pydantic is a plus; PydanticAI is a strong advantage)
Solid experience in building and optimizing ETL/ELT pipelines
Very good knowledge of SQL and relational databases
Experience with PySpark
Familiarity with dbt is a plus
Experience with Azure Data Services is an advantage
Knowledge of CI/CD practices and tools (e.g. GitHub)
General understanding of infrastructure, orchestration, and IT security principles
Proven experience in Data Engineering (Regular level)
Bachelor’s or Master’s degree in a technical field (e.g. Computer Science, Engineering) or equivalent experience
Fluent English (written and spoken)
DevOps mindset (“you build it, you run it”)
Ability to understand complex requirements and translate them into actionable solutions
Strong communication skills and ability to work with cross-functional teams
Attention to detail, especially regarding data quality and business logic
Proactive attitude, ownership, and willingness to learn new technologies
Experience in the insurance domain is a plus
Mile widziane:
Familiarity with dbt
Experience with Azure Data Services
Experience in the insurance domain
O projekcie:
We are looking for a Regular Data Engineer to join a new, innovative project for one of our key clients in the insurance industry. You will work in a hybrid model with teammates based in Poland and collaborate with global stakeholders, including direct interaction with business users. This project focuses on building an advanced solution leveraging Large Language Models (LLMs) to scan documents and support automated decision-making processes.
Zakres obowiązków:
Contribute by building a training dataset for document processing and decision support
Design and implement end-to-end data pipelines (ingestion, transformation, storage, and consumption)
Prepare and maintain high-quality training datasets for machine learning models
Work with large-scale data on a modern cloud data platform (Databricks)
Apply best practices in data engineering, testing, and deployment
Collaborate closely with data scientists, engineers, and business stakeholders
Continuously improve performance, reliability, and automation of data workflow
Oferujemy:
Contract under Polish law: B2B or Umowa o Pracę
Benefits such as private medical care, group insurance, Multisport card
There are English classes available
Hybrid work (at least 1 day/week on-site) in Warsaw (Mokotów)
Opportunity to work with excellent professionals
High standards of work and focus on the quality of code
New technologies in use
Continuously learning and growth
International team
Pinball, PlayStation & much more (on-site)
🔍 Dekoder Ogłoszenia
🔴
DevOps mindset (“you build it, you run it”)
Oczekuje się, że będziesz odpowiedzialny za cały cykl życia kodu, od tworzenia po utrzymanie i rozwiązywanie problemów w produkcji.
🔴
Ability to understand complex requirements and translate them into actionable solutions
Może oznaczać, że wymagania będą niejasne, sprzeczne lub trudne do zrealizowania, a Ty będziesz musiał je doprecyzować.
🔴
Proactive attitude, ownership, and willingness to learn new technologies
Oczekuje się od Ciebie inicjatywy w rozwiązywaniu problemów i samodzielności, nawet jeśli nie masz doświadczenia w danej technologii.
🟡
Proven experience in Data Engineering (Regular level)
Poziom 'Regular' może być interpretowany bardzo szeroko, od kilku lat doświadczenia do osoby samodzielnej, ale bez głębokiej specjalizacji.
🟡
Bachelor’s or Master’s degree in a technical field (e.g. Computer Science, Engineering) or equivalent experience
Określenie 'lub równoważne doświadczenie' daje dużą elastyczność rekruterowi w ocenie kandydatów bez formalnego wykształcenia.