Senior Specialist - Technical Data Engineer (all genders welcome)

at  Kia Europe GmbH

EDUCATION:

• Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, Information Technology, or a closely related discipline.EXPERIENCE:
• 3-5 years of professional experience in data engineering, software development, or a related technical field.
• Solid understanding of data structures, algorithms, databases, and high-level programming languages (e.g., Python, Java, or Scala).
• Experience with cloud platforms, particularly AWS, and familiarity with DevOps practices.
• Proven experience with AWS, including services such as S3, Lambda, RDS, and API Gateway.
• Experience with Open API standards and API development.

SKILLS:

• Proficiency with software development tools such as Git, Jenkins, Jira, and Confluence.
• Strong problem-solving abilities and analytical skills.
• Ability to work independently and manage tasks with minimal supervision.
• Flexibility to adapt quickly to new challenges in a fast-paced environment.
• Good interpersonal skills with a multicultural awareness.
• Excellent verbal and written communication skills in English (working language).
• Knowledge of API development, Open API standards, and experience in the automotive industry are advantageous.

WHO ARE WE?

Kia Connect was founded in 2019 as a fully owned subsidiary of Kia Europe and is therefore part of the fifth-largest automotive group in the world.
Kia is a global mobility brand with a vision to create sustainable mobility solutions for consumers, communities, and societies around the world. Founded in 1944, Kia has been building motorcycles, cars and trucks for more than 75 years.
Kia is now spearheading the popularization of electrified and battery electric vehicles, developing a growing range of mobility services while encouraging millions of people to explore the best ways of getting around. Our brand slogan – ‘Movement that inspires’ – reflects our commitment to inspire consumers through our products and services.
Our European headquarter that we closely cooperate with, Kia Europe, is the European sales and manufacturing arm of Kia Corporation. From our headquarters in Frankfurt, Germany, we lead 39 markets across Europe and the Caucasus, employing more than 5,500 persons, including about 3,500 blue collar workers in our state of the art car plant in Žilina, Slovakia.
Our headquarter is home to 37 different nationalities and this diversity is truly inspiring! This means that every day at Kia is an opportunity to learn something new and to grow personally and professionally. The mix of ambitious and dynamic employees from all over the world is the fuel to our success. Do you have what it takes to join our team? We are looking forward to getting to know you!

• Data Architecture: Create solution architectures, including system diagrams, technical specifications, and implementation plans for data infrastructure and services.
• API Development: Work on Open API standards and develop APIs that are easy to use, well-documented, and meet the requirements of our developer portal for Automotive OEMs.
• Data Pipeline Management: Design, build, and manage data pipelines to ensure efficient and reliable data flow from various sources to the data warehouse or data lakes.
• Cloud Infrastructure: Implement and manage cloud-based data infrastructure, primarily on Amazon Web Services (AWS), ensuring scalability, security, and performance.
• Risk Mitigation: Help identify, communicate, and mitigate risks and issues related to data engineering projects and integration solutions.
• Technical Support: Provide guidance and support to project teams during all phases of data engineering projects, ensuring alignment with best practices and architectural guidelines.
• Technology Evaluation: Participate in evaluating and selecting appropriate technologies to meet project objectives, focusing on data services, API development, and cloud-based solutions.
• Project Coordination: Assist in project management and coordination, working closely with cross-functional teams to ensure successful delivery of data solutions.
• Development Collaboration: Collaborate with development teams to ensure that architectural guidelines and best practices are followed during the implementation of data pipelines, APIs, and other data services.
• Code Review: Review design proposals and code changes to improve the maintainability, testability, readability, and extensibility of data solutions.
• Process Improvement: Implement and promote best practices in data engineering and agile methodologies to enhance the quality and efficiency of data services