Streaming Platform Engineer

On; Deutschland; Vor Ort; EUR 60.000 - 90.000; Vollzeit

Zusammenfassung

On is seeking a passionate Streaming Data Engineer to lead the development of a real-time data streaming platform. This role requires expertise in streaming technologies and cloud platforms to drive innovation within the organization. You will collaborate with a talented team to ensure high-quality, reliable data pipelines that enhance decision-making and efficiency. Join us in supporting a fair and inclusive work environment that emphasizes growth and well-being.

Leistungen

Supportive, team-oriented atmosphere

Access to personal self-care for well-being

Qualifikationen

• Experience with Kafka, Flink, or Spark Streaming.
• Familiarity with GCP Pub/Sub or AWS Kinesis.
• Strong interpersonal skills for stakeholder relationships.

Aufgaben

• Contribute to the strategy of the streaming data platform.
• Design and develop a scalable data infrastructure.
• Implement processes ensuring data quality and reliability.

Kenntnisse

Streaming Technologies

Cloud-Based Platforms

Communication

Jobbeschreibung

In the dynamic landscape of On, data plays a crucial role in accelerating our business growth and operations. We are enhancing our technology landscape to fuel the growth of On, helping to ignite the human spirit through movement.

Your Mission

1. Build the Future of Real-Time Data at On: Contribute to the execution and strategy of our streaming data platform, identifying opportunities to leverage real-time data to drive innovation and efficiency across the organization.
2. Champion Streaming Solutions: Be a passionate advocate for the power of real-time data and stream processing, effectively communicating its potential and benefits to stakeholders across the technology organization.
3. Design and Develop Scalable Infrastructure: Contribute to the design, development, and implementation of a robust and scalable streaming data platform to support On's growing data needs. This includes technologies like Kafka, Flink, Spark Streaming, or similar.
4. Ensure Data Quality and Reliability: Implement processes and tools to ensure the quality, reliability, and availability of real-time data pipelines.
5. Enable Collaboration: Work closely with software engineers, data engineers, data scientists, and other teams to integrate streaming solutions into On's data ecosystem.
6. Embrace New Technologies: Stay abreast of the latest advancements in stream processing technologies and contribute to the continuous improvement of On's data platform.

Your Story

1. Passionate about Streaming Technologies: You possess a keen interest in stream processing concepts, architectures, and technologies. You have experience with a major streaming platform (e.g., Kafka, Flink, Spark Streaming) and building and maintaining production-level streaming data pipelines.
2. Cloud and Platform Expertise: You are familiar with stream-processing solutions on cloud-based platforms (e.g., GCP Pub/Sub, AWS Kinesis).
3. Communication and Collaboration: You have good communication and interpersonal skills, enabling you to build strong relationships with stakeholders across the organization.

Meet The Team

You will be part of a talented and diverse team of data engineers, data scientists, and product managers focused on revolutionizing the use of stream-processing across the organization. We are building innovative data solutions to optimize internal processes, enhance customer experiences, and drive business growth.

What We Offer

On is a place that is centered around growth and progress. We offer an environment designed to give people the tools to develop holistically - to stay active, to learn, explore, and innovate. Our distinctive approach combines a supportive, team-oriented atmosphere, with access to personal self-care for both physical and mental well-being, so each person is led by purpose. On is an Equal Opportunity Employer. We are committed to creating a work environment that is fair and inclusive, where all decisions related to recruitment, advancement, and retention are free of discrimination.