Data Engineer - Automation & Innovation Department

Our requirements

• Minimum 3 years of experience in a Data Engineering role.
• Practical experience with Cloud (preferably GCP) services, including BigQuery, Dataflow, Google Cloud Storage (GCS), Data Catalog, and dbt.
• Advanced SQL proficiency, including writing complex queries, query optimization, Common Table Expressions (CTEs), window functions, and related advanced SQL techniques.
• Python coding skills (experience with Pandas and NumPy is a plus)
• Experience working with Apache Airflow for pipeline orchestration, workflow automation, monitoring, data quality validation, alerting, and troubleshooting.
• Experience with Apache Spark, Hadoop, and Hive for large-scale data processing.
• Experience designing, developing, testing, maintaining, and optimizing ETL/ELT pipelines for batch and streaming data processing, including Apache Kafka, API-based data ingestion.
• Experience designing and implementing data integration solutions, data warehouse architectures, data models, and data layers to support analytics and reporting.
• Experience implementing and maintaining CI/CD pipelines and using GitLab for version control and technical documentation.
• Experience working in Agile/Scrum
• Good command of English.

Optional

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Economics, or a related field.
• Basic understanding of Machine Learning and MLOps principles
• Strong understanding of data governance principles, including metadata management and data quality frameworks.
• Experience in international or multi-country data projects is preferred.
• Strong communication skills to translate technical findings into business-oriented insights.
• Self-starter with a continuous learning mindset and strong attention to detail.

Your responsibilities

• Build and maintain data ingestion processes from various sources into the Data Lake.
• Design, develop, and optimize complex data pipelines for reliable data flow.
• Build, develop, and maintain frameworks that facilitate the construction of data pipelines.
• Implement end-to-end testing frameworks for data pipelines.
• Collaborate with data analysts and scientists to ensure the delivery of quality data.
• Ensure robust data governance, security, and compliance practices.
• Explore and implement emerging technologies to improve data pipeline performance.
• Utilize and integrate data from various source system types, including Kafka, MQ, SFTP, databases, APIs, and file shares

About the project

Benefits

• sharing the costs of sports activities
• private medical care
• sharing the costs of professional training & courses
• life insurance
• flexible working time
• corporate products and services at discounted prices
• mobile phone available for private use
• no dress code
• parking space for employees
• employee referral program
• charity initiatives

Recruitment stages

• 1.
  Wyślij swoje CV
• 2.
  Spotkaj się z przyszłym liderem/ liderką zespołu :)
• 3.
  Witaj w T-Mobile :)

T-Mobile