Data Engineer

at  thyssenkrupp Components Technology Hungary Kft

Company
Thyssenkrupp is an international industrial and technology company employing around 100,000 people. Across 48 countries it generated sales of 38 billion in fiscal 2022/2023. Backed by extensive technological know-how, the businesses develop cost-effective and resource-friendly solutions to the challenges of the future, mainly in the fields of climate protection, the energy transition, digital transformation in the industry and mobility of the future. Under the thyssenkrupp umbrella brand the company creates long-term value with innovative products, technologies and services and contributes to a better life for future generations.
In the Hungarian development center with our engineering team of 1000 we are present as an innovative and significant partner in one of the fastest growing and most exciting segment of the automotive industry, in the field of electromechanical steering systems. With outstanding quality and high-tech developments we meet the needs of renowned car manufacturers and our developments can be found in 25 % of the manufactured cars all over the world. Our engineers work on new challenges that can change the future of automotive.

TECHNICAL SKILLS:

• Python: Proficiency in Python for data processing, scripting, and automation. Experience with libraries such as Pandas, NumPy, and SQLAlchemy.
• SQL: Strong expertise in SQL for querying, database management, and performance tuning. Experience with relational databases like MySQL, PostgreSQL, or SQL Server.
• ETL Tools: Experience with ETL tools and frameworks such as Apache Airflow or Kafka would be beneficial
• Data Warehousing: Knowledge of data warehousing concepts and experience with data warehouse solutions like Snowflake.
• Cloud Platforms: Experience with cloud platforms such as AWS, GCP, or Azure for data storage, processing, and deployment.
• Version Control: Proficiency with version control systems like Git.

SOFT SKILLS:

• Problem-solving: Strong analytical and problem-solving skills.
• Communication: Excellent verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders.
• Team Collaboration: Ability to work effectively in a team-oriented environment and collaborate with cross-functional teams.
• Attention to Detail: High attention to detail and a commitment to data accuracy and integrity.

• Design, develop, and maintain scalable data pipelines: Create and optimize ETL processes to ensure efficient data flow from various sources into our data warehouse and analytics systems.
• Data management: Ensuring data integrity, performance, and security. Implement and maintain database solutions using SQL and NoSQL databases.
• Data integration: Integrate data from multiple sources, including APIs, third-party services, and internal systems.
• Collaborate with data teams: Work closely with data scientists, analysts, web application developers and other stakeholders to understand their data needs and ensure data is readily available and accessible.
• Data quality and governance: Implement data quality checks, monitoring, and validation processes to ensure the accuracy and reliability of data.
• Performance optimization: Analyze and optimize query performance and storage solutions to handle large-scale datasets efficiently.
• Documentation and best practices: Document data processes, pipelines, and systems. Promote best practices for data engineering and data management within the team.