Lead/ Senior GCP Data Engineer with Airflow
Opis oferty pracy
Niniejsze ogłoszenie dotyczy pracy w firmie Xebia
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We are Xebia – a place where experts grow. For nearly two decades now, we’ve 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.
Zakres Obowiązków i odpowiedzialności
- developing and maintaining data pipelines to ensure seamless data flow from the Loyalty system to the data lake and data warehouse,
- collaborating with data engineers to ensure data engineering best practices are integrated into the development process,
- ensuring data integrity, consistency, and availability across all data systems,
- integrating data from various sources, including transactional databases, third-party APIs, and external data sources, into the data lake,
- implementing ETL processes to transform and load data into the data warehouse for analytics and reporting,
- working closely with cross-functional teams including Engineering, Business Analytics, Data Science and Product Management to understand data requirements and deliver solutions,
- collaborating with data engineers to ensure data engineering best practices are integrated into the development process,
- optimizing data storage and retrieval to improve performance and scalability,
- monitoring and troubleshooting data pipelines to ensure high reliability and efficiency,
- implementing and enforcing data governance policies to ensure data security, privacy, and compliance,
- developing documentation and standards for data processes and procedures.
Wymagane Kompetencje i doświadczenie
- 7+ years in a data engineering role, with hands-on experience in building data processing pipelines,
- experience in leading the design and implementing of data pipelines and data products,
- proficiency with GCP services, for large-scale data processing and optimization,
- extensive experience with Apache Airflow, including DAG creation, triggers, and workflow optimization,
- knowledge of data partitioning, batch configuration, and performance tuning for terabyte-scale processing,
- strong Python proficiency, with expertise in modern data libraries and frameworks (e.g., Databricks, Snowflake, Spark, SQL),
- hands-on experience with ETL tools and processes,
- practical experience with dbt for data transformation,
- deep understanding of relational and NoSQL databases, data modelling, and data warehousing concepts,
- excellent command of oral and written English,
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
🟣 Work from the European Union region and a work permit are required.
Mile widziane
- experience with ecommerce systems and their data integration,
- knowledge of data visualization tools (e.g., Tableau, Looker),
- understanding of machine learning and data analytics,
- certification in cloud platforms (AWS Certified Data Analytics, Google Professional Data Engineer, etc.).
Benefity
✍ Development:
- development budgets of up to 6,800 PLN,
- we fund certifications e.g.: AWS, Azure, ISTQB, PSM,
- access to Udemyand O'Reilly (formerly Safari Books Online),
- events and technology conferences,
- technology Guilds,
- internal training,
- Xebia Upskill.
🩺 We take care of your health:
- private medical healthcare,
- multiSport card - we subsidise a MultiSport card,
- mental Health Support.
🤸♂️ We are flexible:
- flexible working hours,
- B2B or permanent contract,
- contract for an indefinite period.
Etapy rekrutacji
Recruitment Process: CV review – HR call – Technical Interview – Client Interview – Decision
Nota prawna
*Powyższe ogłoszenie zostało opublikowane grzecznościowo przez administrację portalu DigiJobs.pro i nie stanowi oferty w świetle obowiązującego prawa. Portal nie bierze odpowiedzialności za prowadzenie procesu rekrutacyjnego, jedynie cytuje treść oficjalnego ogłoszenia. Aplikowanie na ofertę pracy odbywa się bezpośrednio na stronie Pracodawcy wskazanego w ogłoszeniu lub platformie zewnętrznej wskazanej przez Pracodawcę do tego celu w zewnętrznych źródłach.