Data Engineer - Automation and Innovation Department @ T-Mobile Polska
(práce v Polsku)

Data Engineer - Automation and Innovation Department @ T-Mobile Polska

Polsko

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Economics, or a related field.
• Minimum 3 years of experience as a Data Analyst or Data Quality Analyst in a data-driven organization.
• Proven experience in data quality management and data governance practices.
• Strong database expertise, including advanced SQL and PL/SQL.
• Proficiency in Python, with experience in Scala as a plus.
• Proficiency in cloud platforms and services (preferably GCP).
• Experience with Linux and bash scripting.
• Solid understanding of Cloudera Hadoop technology stack (Apache Spark, Apache Kafka).
• Knowledge of data handling principles, including ETL processes and real-time data processing.

Nice to have:

• Experience with CI/CD pipelines and automation tools.
• Strong understanding of data governance principles, including metadata management and data quality frameworks.
• Ability to work with and understand various source system types (Kafka, MQ, SFTP, databases, APIs, file shares).
• Experience in international or multi-country data projects is preferred.
• Strong communication skills to translate technical findings into business-oriented insights.
• Fluent in English, both written and spoken.
• Self-starter with a continuous learning mindset and strong attention to detail.

We are looking for experienced Data Engineer who will be responsible for designing, implementing, and maintaining scalable data pipelines and infrastructure to ensure seamless data ingestion, storage, and transformation across multiple international environments.

This role operates within a global project context, collaborating with cross-functional teams located in different regions to deliver reliable and high-performance data solutions.

The position emphasizes the technical aspects of data engineering, including optimizing system performance, ensuring data consistency across geographies, and supporting robust, scalable, and compliant data workflows on an international scale.

,[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] Requirements: Degree, Data science, SQL, Python, Linux, Bash, Apache Kafka, Cloudera, Hadoop, Apache Spark, ETL, Cloud platform, Scala, GCP, CD pipelines, Data management, Kafka, IBM MQ, SFTP, Communication skills

Kategorie

data

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