Senior Data Engineer (all genders)

Description

Join the global team of experts at the company, which works across software, data and AI to build digital products, services and operating models with measurable business impact.

The company has 2,500 experts across its international teams, who help build, run and scale intelligence across the full value chain.

The role is based at the Berlin data studio, and the primary location is Berlin.

The company's hybrid workplace offers a high degree of flexibility, and it puts people and genuine human connections first in a supportive, inclusive environment.

The data crew publishes project insights, personal perspectives, videos and stories on its blog, along with meetup highlights and upcoming events.

Responsibilities

• Design and build scalable data pipelines that process and analyse large volumes of data efficiently.
• Assess and adopt new data engineering technologies and tools to make data processing faster and more efficient.
• Help customers obtain the data they need easily and transparently so they can build smart data products in mobility, automotive, industrial, consumer, financial and non-profit domains.
• Work with data scientists and analysts to find potential data sources, judge their usefulness and build solutions that meet their data requirements.
• Share your expertise with teammates, contribute to knowledge sharing and team development, and lead technically within the team.
• Write and maintain documentation on data engineering processes, best practices and technologies.

Requirements

• At least 5 years of relevant experience in data engineering.
• Solid knowledge of at least one programming language, such as Python, Java or Scala, and experience with big data technologies such as Hadoop, Spark or Kafka.
• Deep knowledge of batch and real-time data processing frameworks such as Apache Spark, Apache Flink or similar.
• Hands-on experience with cloud data platforms on Azure, AWS or GCP, plus an understanding of data modelling and architecture and experience with Databricks.
• Experience providing technical leadership and advising clients on technical concepts.
• Full professional proficiency in German and English, at C1 level minimum.
• Knowledge of building machine learning pipelines and models.
• Experience managing projects with agile methods such as SAFe, Scrum or Kanban.
• Familiarity with DataOps practices and DevOps concepts.
• Experience implementing data quality and data governance frameworks.

Conditions

Hybrid work model with a primary location in Berlin.

Equal opportunity: every application is welcomed and considered equally, and the company opposes discrimination and harassment based on any protected characteristic.

Benefits

• Professional and personal growth through training programmes, free language courses, competence centres and an active tech community.
• Work-life balance through hybrid work, workation, flexible hours, parental support and sabbaticals.
• Engagement in the Sustainability Hub, diverse communities, the Diversity Taskforce and after-work activities.
• Public transport tickets, job bikes, exclusive Volkswagen employee conditions on vehicle leasing or purchase, health offers, supplementary insurance, a pension plan and various discounts.