Data Engineer

Who are we? Zeta Global is seeking a talented and versatile Data Engineer to join our Data Exchange team within our highly skilled development office in Copenhagen. This team plays a critical role in developing and deploying Zeta’s next-generation data science and engineering technology, collaborating closely with our global teams in the US, Europe, India and Philippines. The Copenhagen office boasts a dynamic and focused environment, comprising a core group of start-up veterans and approximately 30 highly skilled professionals. As a member of the Data Exchange team, you will contribute to the analysis, development, and maintenance of our complex data infrastructure, a sophisticated ecosystem of interconnected systems. This team tackles a continuous stream of challenging projects originating from across the organization, demanding a high degree of expertise and innovation. We are seeking candidates with a strong foundation in data engineering, data analysis, and software development principles, and a demonstrated interest in exploring the intersections between these disciplines. The Company Zeta Global is a data and AI-powered marketing technology company built on the foundation of a robust consumer data platform. With billions of proprietary data points and sophisticated machine learning algorithms, Zeta helps marketers unlock actionable insights into consumer behavior and preferences. The company's Zeta Marketing Platform harnesses this powerful combination of data and AI to create personalized customer experiences across the entire customer journey, ultimately driving significant growth for its clients. Through a commitment to innovation in data science, Zeta Global provides enterprises with the tools they need to build meaningful and profitable customer relationships. The position The ideal candidate for the Data Engineer position at Zeta Global Copenhagen is a highly motivated and analytical individual with a passion for understanding complex (software) systems. You are adept at using data to identify issues, formulate solutions, and develop robust data pipelines and software. You thrive in an environment that offers significant autonomy in planning and executing your work, yet you are also a strong collaborator, readily engaging with fellow developers and international product stakeholders. You will be involved in every stage of the development process, from initial brainstorming to ongoing maintenance, with a primary emphasis on analysis, prototyping, and development. Our development process is a dynamic blend of agile and rapid prototyping methodologies, designed to foster a culture of "flexibility under responsibility." We prioritize focused development time and believe in the power of collaborative problem-solving, encouraging team members to both seek and offer assistance readily. Your profile We welcome candidates with a solid background in data analysis or software development, seeking professionals with proven experience or recent graduates. Regardless of your background, a crucial element is your intellectual curiosity, self-motivation, and a demonstrable ability to translate real-world challenges into data models, ETL processes, algorithms, and ultimately, functional code. A strong interest in data engineering and/or the AdTech domain, along with its associated technologies, is highly desirable, as well as knowledge of object-oriented programming languages, particularly Scala. Minimum Qualifications : A strong academic background in a quantitative field (Computer Science, Mathematics, Physics, or related disciplines). Hands-on experience in designing, building, and maintaining scalable and reliable data pipelines. Proficiency in Python, Scala or other OOP languages for data engineering and processing tasks. Strong data analysis skills, including working with large datasets. Knowledge of distributed data processing for batch workloads. Solid understanding of database technologies. Desired Qualifications: 2-3 years of experience with Scala for data processing. Strong software engineering skills, including experience with CI/CD pipelines and best coding practices. Familiarity with data integrations and efficient data transfers. Knowledge of data modeling, data warehousing concepts, and query optimization techniques. Experience with distributed data processing using Apache Spark. Experience with Airflow for workflow orchestration, scheduling, and monitoring data pipelines. Cloud expertise, particularly AW