Lead Data Engineer (m/f/d)

Deutsche Telekom IT Solutions Slovakia

1d•Remote

About The Position

As a Lead Data Engineer, the purpose of this role is to manage and oversee the entire data engineering process, from data acquisition to data analysis. The position is responsible for designing, building, and maintaining the data infrastructure necessary for effective data management and analysis. The role involves working closely with data scientists, analysts, and other stakeholders to ensure the accuracy, reliability, and accessibility of data. It also includes mentoring and leading a team of data engineers, setting technical direction, and ensuring the successful delivery of data engineering projects.

Requirements

5 years experience at ICT Analysis, Architecture & Design
Master degree in information technologies
Python - expert
NoSQL/SQL database - expert
Spark - intermediate
Hadoop - intermediate
Clouds (AWS, GPC, Azure) - advanced
Kafka - advanced
ETL/ELT - advanced
Data Warehouse - advanced
Big Data - advanced
Analytical skills
Problem solving skills
Effective communication
Presentation skills
Cross functional collaboration
Ability to innovate
Team management
Project management
Agile methodology
English - advanced (C1)
A Master's or PhD degree in a technical field, such as computer science, statistics, or mathematics, telecommunications.
At least 7 years of experience in a data engineering role, with a strong track record of delivering scalable and efficient data systems.
Strong programming skills, including experience with Python, Java, Scala, or other relevant programming languages.

Nice To Haves

German - advantage

Responsibilities

Design, build, and maintain scalable and efficient data systems, leveraging big data technologies
Lead the data engineering team and manage the project roadmap, ensuring projects are delivered on time and within budget.
Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to understand and meet their data needs.
Design and implement data pipelines to ingest, process, and store large and complex data sets, ensuring the reliability and performance of the data systems.
Implement data security and privacy controls, following industry best practices and company policies.
Monitor and optimize the performance of data systems, proactively identifying and resolving bottlenecks and issues.
Stay up-to-date with emerging trends and technologies in the field of data engineering, and evaluate their potential impact on the company.
Mentor and guide junior data engineers, providing technical and professional development opportunities to help them grow in their careers.