Salary for Senior-level / Expert Data Engineer in Germany during 2024

Salary details

The average senior-level / expert Data Engineer salary lies between USD 96,888 and USD 287,000 in Germany. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Jan. 12, 2025

Top 20 Job Tags for Senior-level / Expert Data Engineer roles

The three most common job tag items assiciated with senior-level / expert Data Engineer job listings are Engineering, Python and SQL. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Engineering | 8809 jobs Python | 8409 jobs SQL | 8243 jobs Pipelines | 7457 jobs AWS | 5827 jobs Data pipelines | 5736 jobs ETL | 5647 jobs Architecture | 5497 jobs Spark | 5259 jobs Computer Science | 4829 jobs Big Data | 4331 jobs Azure | 4301 jobs Agile | 3981 jobs Security | 3816 jobs Machine Learning | 3581 jobs Java | 3334 jobs Data quality | 3331 jobs GCP | 3155 jobs Airflow | 3153 jobs Snowflake | 3029 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Data Engineer job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 6855 jobs Health care | 3681 jobs Flex hours | 2968 jobs Team events | 2175 jobs Startup environment | 2101 jobs Competitive pay | 2040 jobs Equity / stock options | 1910 jobs Flex vacation | 1700 jobs Salary bonus | 1698 jobs Insurance | 1546 jobs Parental leave | 1469 jobs Medical leave | 1272 jobs Wellness | 964 jobs 401(k) matching | 841 jobs Fitness / gym | 421 jobs Gear | 374 jobs Home office stipend | 350 jobs Transparency | 346 jobs Conferences | 294 jobs Relocation support | 292 jobs

Salary Composition

In Germany, the salary composition for a Senior-level or Expert Data Engineer in AI/ML/Data Science typically includes a mix of fixed salary, bonuses, and additional remuneration. The fixed salary often constitutes the majority of the total compensation package, usually ranging from 70% to 85%. Bonuses, which can be performance-based or company-wide, might account for 10% to 20% of the total salary. Additional remuneration could include stock options, especially in tech companies or startups, and other benefits like health insurance, retirement contributions, and transportation allowances. The exact composition can vary significantly depending on the region, with cities like Berlin and Munich offering higher salaries due to the cost of living. Industry also plays a role; for instance, finance and tech sectors tend to offer more competitive packages. Larger companies might provide more comprehensive benefits compared to smaller firms or startups.

Increasing Salary Further

To increase your salary beyond the current median, consider the following strategies:

• Specialization: Develop expertise in niche areas of data engineering, such as real-time data processing or cloud-native data solutions, which are in high demand.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Engineering Manager or Director of Data Engineering, which typically offer higher salaries.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML and data science. This could involve taking advanced courses or attending industry conferences.
• Networking: Build a strong professional network within the industry. This can lead to opportunities in higher-paying companies or roles.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during performance reviews or when switching jobs.

Educational Requirements

For a Senior-level Data Engineer position, a bachelor's degree in Computer Science, Information Technology, or a related field is typically required. However, many employers prefer candidates with a master's degree or even a Ph.D., especially for expert roles. Advanced degrees in Data Science, Machine Learning, or Artificial Intelligence can be particularly advantageous. Additionally, a strong foundation in mathematics and statistics is often essential.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

• Certified Data Management Professional (CDMP)
• Google Professional Data Engineer
• AWS Certified Big Data – Specialty
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Professional (CCP) Data Engineer

These certifications can validate your skills in specific technologies and platforms, making you more attractive to potential employers.

Required Experience

Typically, a Senior-level Data Engineer is expected to have at least 5 to 10 years of experience in data engineering or related fields. This experience should include a proven track record of designing, building, and maintaining scalable data architectures. Experience with big data technologies (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure, Google Cloud), and data warehousing solutions is often required. Additionally, experience in leading projects or teams can be beneficial.

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