Exmox is a Hamburg based AdTech company, building next generation performance marketing products. It is our mission to connect advertisers with their highest value users through our owned and operated products. We have created an innovative business model that focuses on rewarding users for testing and engaging with the products of our clients. We are proud to call some of the biggest mobile gaming companies our clients.
We’re in the scale up phase and are looking for new talents who are eager to contribute to our growth.
Are you ready to make an impact? Become part of our growing team and help shape the future of performance marketing.

Tasks

• Design, develop, and maintain scalable ETL pipelines on Databricks to integrate data from various sources, including app / web products, and marketing partner data.
• Build and manage the DataLakehouse on Databricks from the ground up, including migrating legacy data products. Implement data transformations and processing logic using Databricks and PySpark to ensure efficient data handling and analysis.
• Monitor and maintain the data stack for nightly and near-real-time processing of in-house tracking solutions, ensuring high performance and reliability. Continuously optimize and troubleshoot data pipelines to ensure data quality and integrity.
• Collaborate with cross-functional teams to ensure seamless data flow and integration into the DataLakehouse. Provide Tableau support for data analysts as needed.
• Stay updated with industry best practices and emerging technologies in data engineering.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems or related field is preferred -or- Bootcamp experience with a minimum of 3 years professional experience.
• Proficiency in designing, implementing, and optimizing ETL processes, also orchestrating ETL workflows.
• Hands-on experience with DataBricks and AWS services (e.g., S3, Kinesis, Lambda) or similar technologies.
• Strong proficiency in Python, SQL, and PySpark for data manipulation and processing.
• Knowledge of data integration and data quality best practices.
• Experience with GitLab CI/CD pipelines is a plus.
• Familiarity with PostgreSQL is a plus.
• Excellent problem-solving skills and attention to detail.
• Ability to work independently and collaborate effectively in a team environment.
• Strong communication and interpersonal skills.
• Fluent English in both verbal and written skills.

Benefits

• Work Life Balance

We value rest and work life balance, we offer you 30 days of paid vacation days

• Commuter Benefits

We provide you with public transportation tickets

• Professional Development

We support you in deepening your skills and provide you an annual education budget of 1.500€

• Workation

Combine Vacation with work: we offer annual workation opportunities

• Gym membership - Wellpass

With Wellpass you can use more than 7000 Spas/ Gyms/ etc. in Germany

• Catering

We offer monthly team lunches, daily fruits and vegetables and every beverage you could wish for

• Flexibility

Benefit from flexible working hours and working from home

• Diversity

We are an international team of talented people with different cultural backgrounds

• Fun and Games

We have a big socializing area to make room for having relaxing activities within the working day

• Desk Setup

Wherever you work, we will provide you with your workspace utensils
Please note: this is not a remote only position, we offer you a flexible hybrid model here in Hamburg, Germany - working from home on Mondays & Fridays, coming to the office on Tuesday, Wednesday & Thursday! : )
This fits your ideas exactly or you’re still unsure if it’s really the right fit? Feel free to contact Alessia and together we will find out. :

• Design, develop, and maintain scalable ETL pipelines on Databricks to integrate data from various sources, including app / web products, and marketing partner data.
• Build and manage the DataLakehouse on Databricks from the ground up, including migrating legacy data products. Implement data transformations and processing logic using Databricks and PySpark to ensure efficient data handling and analysis.
• Monitor and maintain the data stack for nightly and near-real-time processing of in-house tracking solutions, ensuring high performance and reliability. Continuously optimize and troubleshoot data pipelines to ensure data quality and integrity.
• Collaborate with cross-functional teams to ensure seamless data flow and integration into the DataLakehouse. Provide Tableau support for data analysts as needed.
• Stay updated with industry best practices and emerging technologies in data engineering