About this role
Analytical engineers who enjoy understanding complex software systems and working with significant autonomy will thrive in this environment. Zeta Global is seeking a Data Engineer to join the Data Exchange team inside the development office in Copenhagen. This group of approximately thirty professionals builds next-generation data science and engineering technology while collaborating with global teams in the US, Europe, India, and the Philippines.
Daily responsibilities involve analyzing, developing, and maintaining a sophisticated ecosystem of interconnected systems. Team members handle a continuous stream of challenging projects from across the organization, participating in every stage of development from brainstorming to ongoing maintenance with a focus on prototyping and engineering.
The role exists to support the company's data and AI-powered marketing technology platform, which processes billions of proprietary data points. Ideal candidates bring a strong foundation in data engineering, data analysis, or software development, combined with intellectual curiosity and the ability to translate real-world challenges into functional code.
What you will do
- Contribute to the analysis, development, and maintenance of a complex data infrastructure and interconnected systems.
- Engage in every stage of the development process, placing primary emphasis on analysis, prototyping, and engineering.
- Translate real-world challenges into data models, ETL processes, algorithms, and functional code.
- Design, build, and maintain scalable and reliable data pipelines for large datasets.
- Collaborate closely with fellow developers and international product stakeholders across multiple global offices.
- Approach problems with an analytical mindset while maintaining a pragmatic approach to solution development.
What you need
- Hold a strong academic background in a quantitative field such as Computer Science, Mathematics, Physics, or a related discipline.
- Possess hands-on experience in designing, building, and maintaining scalable and reliable data pipelines.
- Demonstrate proficiency in Python, Scala, or other object-oriented programming languages for data engineering tasks.
- Exhibit strong data analysis skills, including the ability to work effectively with large datasets.
- Show knowledge of distributed data processing for batch workloads alongside a solid understanding of database technologies.
- Possess excellent English communication skills to enable effective collaboration with international management and colleagues.
Nice to have
- 2-3 years of experience with Scala for data processing
- Experience with CI/CD pipelines and best coding practices
- Familiarity with Apache Spark, Airflow, and cloud services on AWS
- Knowledge of data modeling, data warehousing, and query optimization techniques
Benefits
- Flexible work arrangements including adjustable office hours
- Possibility of occasional remote work
- Freedom to select preferred operating systems and development tools
- Opportunities for cross-departmental collaboration and career advancement
Skills and tech stack
Questions candidates ask
What is the remote work policy for this role?
The company offers flexible work arrangements, which include adjustable office hours and the possibility of occasional remote work, provided commitments are consistently fulfilled.
What tools and technologies will I be using?
Engineers work with Python, Scala, Apache Spark, Airflow, and AWS services such as S3, Glue, Athena, and EMR. Team members also have the freedom to select their preferred operating system and development tools.
What is the team environment like?
The Copenhagen office features a dynamic and focused environment comprising a core group of startup veterans and approximately 30 highly skilled professionals. The group includes many holders of Master's and PhD degrees in fields like Physics, Math, and Computer Science.
What does the hiring process involve?
Interested candidates apply via LinkedIn by submitting a cover letter along with their application. Interviews are scheduled on a continuous basis.