Data Engineer

About The Company

The Deutscher Landwirtschaftsverlag GmbH (dlv) is the leading media company in Europe dedicated to the subjects of agriculture and nature. With a portfolio comprising over 40 media brands, dlv holds a prominent position in its core segments, including agriculture, forestry, hunting, and beekeeping. The company generates an annual revenue exceeding 80 million euros and maintains a strong presence across 18 countries in Europe and North America through its subsidiaries and investments.

As a data-driven media enterprise, dlv combines journalistic excellence with digital innovation to serve its diverse audience and clients effectively.

As a Data Engineer (m/w/d) at dlv, you will be instrumental in building, enhancing, and maintaining our data infrastructure. Your responsibilities will span from designing data models and architecture to deploying high-performance, production-ready data pipelines. You will play a critical role in translating business needs into scalable data solutions, making informed technical decisions based on thorough trade‑off analysis rather than current trends.

The position offers an exciting opportunity to work within a team dedicated to transforming complex data landscapes into modern, efficient, and scalable data platforms.

This role is based in Munich, with a hybrid work model that combines on‑site and remote work, providing flexibility to balance professional and personal commitments. The employment is initially limited to two years, offering a chance to contribute significantly to the company's data initiatives and grow your expertise within a dynamic environment.

The ideal candidate holds a completed degree in Computer Science, Mathematics, Natural Sciences, or a comparable qualification. You have several years of professional experience as a Data Engineer, particularly in environments involving Data Warehouses, Data Lakes, or Lakehouse architectures. Your technical proficiency includes advanced SQL skills, including query tuning, execution plan analysis, indexing, and partitioning, with practical experience in systems such as PostgreSQL.

Additionally, you bring hands‑on experience with No

SQL databases like MongoDB, Cassandra, DynamoDB, or Redis.

You possess strong Python programming 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)---and familiarity with modern architectural approaches like Medallion, Data Mesh, and Lakehouse are essential. Experience working with cloud platforms, especially Microsoft Azure, and familiarity with Microsoft Fabric are highly desirable. Proficiency in Power BI, including DAX, semantic modeling, and Row‑Level Security, is also required.

• Develop and implement conceptual, logical, and physical data models, including Star and Snowflake schemas, with an emphasis on Data Vault where applicable. Evaluate and recommend suitable data architectures such as Lakehouse, Medallion, or Data Mesh based on project requirements, providing justified technical guidance.
• Assess various storage solutions, including relational, document, key‑value, graph, and vector databases, considering factors like consistency, scalability, and cost‑efficiency to select the most appropriate technology for each use case.
• Work proficiently with SQL, optimizing queries, managing execution plans, indexing, and partitioning to ensure efficient data retrieval and processing. Extend expertise to No
  
  SQL systems like MongoDB, Cassandra, DynamoDB, or Redis to handle diverse data types and workloads.
• Design, build, and operate data pipelines for batch and streaming data ingestion, with practical experience in Kafka, including topics, partitioning, consumer groups, schema registry, and ensuring exactly‑once processing semantics.
• Leverage Power BI for advanced reporting and analytics, utilizing DAX, semantic modeling, and implementing Row‑Level Security to deliver tailored insights across the organization.

• Generous holiday entitlement of 30 days plus additional special leave days such as Christmas Eve and New Year's Eve
• Company pension scheme to secure your future
• Pet‑friendly office environment with office dogs
• Performance‑based financial bonuses
• Access to corporate fitness programs, including Wellpass
• Flexible working hours to support work‑life balance
• Support for mental health and well‑being initiatives
• Customized professional development and training programs
• Participation in Job Rad bicycle leasing scheme
• Exclusive employee discounts and corporate benefits
• Hybrid working model combining on‑site presence and remote work within Germany
• Team‑building events and company outings
• Employer-sponsored capital formation benefits (VWL)
• Workation opportunities for remote work in inspiring location slum