Senior Data Engineer (f/m/x) at exmox

Berlin, Berlin, Germany -

Full Time

Start Date

Immediate

Expiry Date

28 Dec, 26

Salary

50000.0

Posted On

29 Sep, 26

Experience

4 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Industry

Information Technology & Services

Description

This is a company built for growth.

When you join exmox, you're stepping onto a global, highly competitive playing field, building high-performing consumer products in mobile gaming. We're scaling a rewarded user engagement and acquisition platform that helps publishers acquire and retain players, and here, data isn't just analyzed, it's turned into systems that directly drive business performance.

As a Senior Data Engineer (f/m/x), you'll operate at the intersection of data, engineering, and product, building and scaling the data foundation that powers our entire business. This isn't a role for maintaining pipelines or following predefined processes, we look for engineering mindset and entrepreneurial ownership: you build it, you own it, and you see the impact in production. We're embracing AI as part of how we work too, using it to cut repetitive tasks and focus where it actually moves the needle.

If you're excited by complex systems, high traffic, and data-driven decisions, and impact matters more to you than process, we want to hear from you. We use AI for everything in order to improve speed and quality.

What you’ll own

Data pipelines & integration You design, develop, and maintain scalable ETL pipelines on Databricks to integrate data from various sources including app and web products and marketing partner data, ensuring reliable and efficient data flow across the business.
DataLakehouse ownership You build and manage the DataLakehouse on Databricks including migrating legacy data products. You implement data transformations and processing logic using Databricks and PySpark to ensure efficient data handling and analysis.
Monitoring & optimisation You monitor and maintain the data stack for nightly and near-real-time processing of in-house tracking solutions, ensuring high performance and reliability. You continuously optimise and troubleshoot pipelines to ensure data quality and integrity.
Cross-functional collaboration You work closely with cross-functional teams to ensure seamless data flow and integration into the DataLakehouse and provide Tableau support for data analysts as needed.
Staying ahead You stay updated with industry best practices and emerging technologies in data engineering, bringing new ideas and approaches to the team.

What You Bring

Technical foundation You have a degree in Computer Science, Engineering or Information Systems or bootcamp experience with a minimum of 4 years of professional experience in data engineering.
ETL expertise You are proficient in designing, implementing and optimising ETL processes and orchestrating ETL workflows in production environments.
Tools & technologies You have hands-on experience with Databricks and AWS services such as S3, Kinesis and Lambda or similar technologies. Experience with GitLab CI/CD pipelines and familiarity with PostgreSQL are a plus.
AI skills You use AI for next to everything you plan and build.
Programming skills You are highly proficient in Python, SQL and PySpark for data manipulation and processing and write clean, maintainable and production-ready code.
Mindset & communication You have excellent problem-solving skills, strong attention to detail, and the ability to work independently and collaboratively. You are fluent in English both verbally and in writing.

Responsibilities

This is a company built for growth.

What you’ll own

Data pipelines & integration You design, develop, and maintain scalable ETL pipelines on Databricks to integrate data from various sources including app and web products and marketing partner data, ensuring reliable and efficient data flow across the business.
DataLakehouse ownership You build and manage the DataLakehouse on Databricks including migrating legacy data products. You implement data transformations and processing logic using Databricks and PySpark to ensure efficient data handling and analysis.
Monitoring & optimisation You monitor and maintain the data stack for nightly and near-real-time processing of in-house tracking solutions, ensuring high performance and reliability. You continuously optimise and troubleshoot pipelines to ensure data quality and integrity.
Cross-functional collaboration You work closely with cross-functional teams to ensure seamless data flow and integration into the DataLakehouse and provide Tableau support for data analysts as needed.
Staying ahead You stay updated with industry best practices and emerging technologies in data engineering, bringing new ideas and approaches to the team.

What You Bring

Technical foundation You have a degree in Computer Science, Engineering or Information Systems or bootcamp experience with a minimum of 4 years of professional experience in data engineering.
ETL expertise You are proficient in designing, implementing and optimising ETL processes and orchestrating ETL workflows in production environments.
Tools & technologies You have hands-on experience with Databricks and AWS services such as S3, Kinesis and Lambda or similar technologies. Experience with GitLab CI/CD pipelines and familiarity with PostgreSQL are a plus.
AI skills You use AI for next to everything you plan and build.
Programming skills You are highly proficient in Python, SQL and PySpark for data manipulation and processing and write clean, maintainable and production-ready code.
Mindset & communication You have excellent problem-solving skills, strong attention to detail, and the ability to work independently and collaboratively. You are fluent in English both verbally and in writing.