Data Engineer Salary in Germany during 2023

Salary details

The average Data Engineer salary lies between USD 77,737 and USD 142,200 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: Nov. 17, 2024

Salary trend

Top 20 Job Tags for Data Engineer roles

The three most common job tag items assiciated with Data Engineer job listings are Python, Engineering and SQL. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Python | 5352 jobs Engineering | 5125 jobs SQL | 5036 jobs Pipelines | 4382 jobs AWS | 3582 jobs Spark | 3309 jobs ETL | 3273 jobs Architecture | 3229 jobs Data pipelines | 3202 jobs Computer Science | 2748 jobs Big Data | 2603 jobs Agile | 2547 jobs Azure | 2406 jobs Java | 2258 jobs Machine Learning | 2077 jobs GCP | 1967 jobs Airflow | 1937 jobs Security | 1845 jobs Scala | 1799 jobs Kafka | 1784 jobs

Top 20 Job Perks/Benefits for Data Engineer roles

The three most common job benefits and perks assiciated with 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 2023 and the number of open jobs that where offering them during that period:

Career development | 4076 jobs Health care | 2146 jobs Flex hours | 2037 jobs Startup environment | 1894 jobs Team events | 1476 jobs Flex vacation | 1326 jobs Competitive pay | 1293 jobs Equity / stock options | 1110 jobs Parental leave | 1062 jobs Salary bonus | 1046 jobs Insurance | 997 jobs Medical leave | 711 jobs Wellness | 645 jobs 401(k) matching | 508 jobs Home office stipend | 375 jobs Fitness / gym | 286 jobs Gear | 275 jobs Unlimited paid time off | 265 jobs Conferences | 199 jobs Relocation support | 148 jobs

Salary Composition

In Germany, the salary composition for a Data Engineer can vary significantly based on factors such as region, industry, and company size. Typically, the salary is composed of a fixed base salary, which forms the bulk of the compensation package. In addition to the base salary, many companies offer performance-based bonuses, which can range from 5% to 20% of the annual salary, depending on the company's performance and individual contributions. Additional remuneration may include stock options, especially in tech startups or larger tech companies, and benefits such as health insurance, retirement plans, and transportation allowances. In regions like Berlin or Munich, where the cost of living is higher, salaries might be slightly elevated compared to other parts of Germany. Similarly, industries such as finance or technology tend to offer higher compensation compared to sectors like education or non-profits.

Steps to Increase Salary

To increase your salary as a Data Engineer, consider the following strategies:

• Skill Enhancement: Continuously update your technical skills, especially in emerging technologies and tools relevant to data engineering, such as cloud platforms (AWS, Azure, Google Cloud), big data technologies (Hadoop, Spark), and data warehousing solutions (Snowflake, Redshift).

• Advanced Education: Pursuing a master's degree or specialized courses in data science, machine learning, or related fields can make you more competitive and open up higher-paying opportunities.

• Networking: Engage with professional networks and communities, attend industry conferences, and participate in meetups to increase your visibility and learn about new opportunities.

• Certifications: Obtain relevant certifications that can validate your skills and expertise, making you more attractive to employers.

• Leadership Roles: Aim for roles with more responsibility, such as team lead or project manager, which often come with higher pay.

Educational Requirements

Most Data Engineer positions require at least a bachelor's degree in computer science, information technology, engineering, or a related field. Some employers may prefer candidates with a master's degree, especially for more senior roles. A strong foundation in mathematics and statistics is also beneficial, as it underpins many data engineering tasks.

Helpful Certifications

Certifications can enhance your profile and demonstrate your expertise to potential employers. Some valuable certifications for Data Engineers include:

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

These certifications validate your skills in specific platforms and tools, which can be crucial for roles that require expertise in those areas.

Experience Requirements

Typically, entry-level Data Engineer positions require 1-3 years of experience in a related field, such as software development or database management. For mid-level roles, 3-5 years of experience is common, while senior positions may require 5+ years of experience, including leadership or project management experience. Practical experience with data modeling, ETL processes, and data warehousing is often essential.

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