Data Engineer

Role overview

This opportunity is being shared for a partner employer that handles the application review and all next steps. The company is hiring a Data Engineer in Germany for a fully remote position.

The role focuses on creating and improving a modern data platform that supports marketing intelligence, customer understanding, and revenue growth across global products. You will work on the full data journey, from collecting and transforming data to making it available for activation and analytics. The work combines hands-on engineering with influence over architecture, data quality, and automation, using cloud tools and AI-supported development practices to deliver dependable data solutions at scale.

Key responsibilities

• Create and support reliable ingestion pipelines that bring data in from REST APIs, SFTP sources, and database replication systems into cloud-based data platforms.
• Develop efficient transformation pipelines in dbt, organized around bronze, silver, and gold layer design patterns.
• Build and maintain data models that support identity matching, audience segmentation, attribution, and marketing activation workflows.
• Integrate external marketing tools and services so data can sync properly, campaigns can run, and feedback can be captured.
• Set up and manage AWS Lambda jobs, Airflow orchestration, and related workflows to keep data operations dependable.
• Add data checks, monitoring, alerts, and validation processes so critical datasets remain accurate and trustworthy.
• Administer cloud infrastructure and platform components through infrastructure-as-code methods using Terraform.
• Troubleshoot and fix data incidents, including failed pipelines, data quality problems, and risks around exposure of sensitive data.
• Help improve engineering standards, automation, documentation, and scalable data architecture over time.

Requirements

• At least 4 years of professional experience building, deploying, and maintaining production data pipelines in Python.
• Strong SQL skills, including advanced querying, query optimization, and performance tuning in cloud data systems.
• Practical experience with Snowflake, including loading data, working with external stages, managing security settings, using warehouses, and improving performance.
• Solid hands-on knowledge of dbt Core for transformations, testing, incremental models, and analytics engineering practices.
• Good understanding of data warehouse design, including dimensional modeling, star and snowflake schemas, facts, dimensions, and slowly changing dimensions.
• Experience creating conceptual, logical, and physical data models.
• Background in building and operating ETL/ELT pipelines with Airflow or similar orchestration tools.
• Comfort using AI-assisted development tools regularly for coding, debugging, and code review.
• Working knowledge of AWS services such as S3, Lambda, IAM, and EventBridge, plus Terraform and CI/CD practices.
• Experience with Git, Docker, data quality tools, and data lineage practices is an advantage.
• Strong analytical problem-solving ability, attention to detail, and comfort working in a remote, collaborative engineering setup.
• Experience with streaming systems, marketing platform integrations, or iGaming products is a plus.

Benefits

• Chance to work on scalable products that have a strong business impact in a growing technology environment.
• Fully remote work arrangement for eligible locations.
• Flexible setup designed to support autonomy and work-life balance.
• Competitive compensation package with performance-based incentives.
• Exposure to modern cloud architecture, data design patterns, and AI-enabled engineering workflows.
• Supportive, collaborative team culture with room for technical growth and professional development.

Application and data notice

Applications are handled by the partner company, while Jobgether manages the matching step. Candidates are shortlisted through an AI-powered process that compares applications against the role requirements, and the shortlist is then shared with the hiring employer. The final hiring decisions, including interviews and assessments, are managed internally by the employer.

By submitting an application, you agree that Jobgether may process your personal data to assess your candidacy and share relevant details with the hiring company. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws, including GDPR. You can exercise your rights to access, correct, delete, or object at any time.

Artificial intelligence tools may also be used to support parts of recruitment, such as reviewing applications, analyzing resumes, or checking responses for inconsistencies or verification signals. These tools assist the recruitment team and do not replace human judgment, and the final decision is always made by people.