Data Engineer

About The Company

The Deutscher Landwirtschaftsverlag GmbH (dlv) is Europe's leading media organization dedicated to the sectors of land and nature. With a portfolio encompassing over 40 media brands, dlv holds a dominant position in core segments such as agriculture, forestry, hunting, and beekeeping. The company generates annual revenues exceeding 80 million euros and maintains a significant presence across Europe and North America through its subsidiaries and partnerships in 18 countries. As a data-driven media enterprise, dlv combines professional expertise with digital innovation to deliver high-quality content and services to its audiences. The organization values sustainability, technological advancement, and a forward-thinking approach to media and information dissemination.

About The Role

We are seeking a highly skilled Data Engineer (m/w/d) to join our dynamic team in Munich on a full-time basis. This role is pivotal in designing, developing, and maintaining our enterprise data infrastructure. You will be responsible for creating scalable, reliable, and efficient data pipelines and architectures that support our analytical and operational needs. Your expertise will help transform complex data into actionable insights, enabling strategic decision-making across the organization. The position involves working closely with cross-functional teams, including data analysts, data scientists, and IT specialists, to ensure seamless data flow and integration. This role is initially limited to two years, offering an exciting opportunity to contribute to innovative data projects within a reputable organization.

Qualifications

The ideal candidate will possess a university degree in computer science, mathematics, natural sciences, or a comparable qualification. You should have several years of professional experience as a Data Engineer, particularly within Data Warehouses, Data Lakes, or Lakehouse architectures. Strong proficiency in SQL, including query optimization, execution plans, indexing, and partitioning, is essential. Additionally, you should have advanced Python skills for data transformation, automation, and deployment in production environments. A solid understanding of data modeling concepts such as dimensional modeling, Data Vault, and schema design (Star/Snowflake) is required, along with familiarity with modern architectural approaches like Medallion, Data Mesh, and Lakehouse. Experience working with cloud platforms, especially Microsoft Azure, and tools like Microsoft Fabric is highly advantageous. Competence in Power BI, including DAX, semantic modeling, and Row-Level Security, is also important.

Responsibilities

• Design and develop conceptual, logical, and physical data models, including star schema, snowflake schema, and Data Vault, aligning them with business requirements and technical standards.
• Evaluate and select appropriate storage solutions such as relational, document, key-value, graph, and vector databases based on consistency, scalability, and cost considerations, providing well-founded recommendations for each use case.
• Work extensively with SQL to perform query tuning, analyze execution plans, optimize indexing, and implement data partitioning strategies, primarily using PostgreSQL and NoSQL systems like MongoDB, Cassandra, DynamoDB, or Redis.
• Design, implement, and operate data pipelines for batch and streaming data, leveraging tools like Kafka for message brokering, including topics, partitioning, consumer groups, schema registry, and ensuring exactly-once processing semantics.
• Utilize Power BI for advanced reporting and analytics, developing DAX measures, semantic models, and implementing security features such as Row-Level Security to ensure data privacy and compliance.
• Collaborate with stakeholders to understand data requirements, translating them into scalable and maintainable data solutions while adhering to best practices and industry standards.
  
  

Benefits

• 30 days of vacation plus additional holiday entitlement for special days such as Christmas Eve and New Year’s Eve.
• Company-sponsored pension scheme to secure your future.
• Pet-friendly office environment, welcoming employees' dogs.
• Performance-based financial bonus to reward your contributions.
• Access to corporate fitness programs, including Wellpass, promoting a healthy lifestyle.
• Flexible working hours to support work-life balance.
• Programs and initiatives aimed at promoting mental health and well-being.
• Personalized training and development programs to support your career growth.
• Participation in JobRad cycling leasing scheme.
• Employee discounts and access to various corporate benefits.
• Hybrid working model allowing for flexible on-site and remote work within Germany.
• Team-building events and company outings to foster a collaborative environment.
• Financial support for commuting via Jobticket subsidies.
• Opportunities for international workations and other innovative work arrangements.
• And many additional perks designed to enhance your employee experience.
  
  

What We Expect From You

• A completed university degree in fields such as computer science, mathematics, natural sciences, or an equivalent qualification.
• Several years of professional experience as a Data Engineer, especially in environments involving Data Warehouses, Data Lakes, or Lakehouse architectures.
• Excellent SQL skills, including query tuning, understanding execution plans, indexing, and data partitioning, with practical experience in PostgreSQL and NoSQL databases like MongoDB, Cassandra, DynamoDB, or Redis.
• Strong Python programming skills for data transformation, automation, and deployment tasks.
• Deep knowledge of data modeling techniques such as dimensional modeling, Data Vault, and schema design (Star/Snowflake).
• Familiarity with modern data architecture concepts like Medallion, Data Mesh, and Lakehouse frameworks.
• Experience working with cloud platforms, particularly