Founding Data Engineer - Analytics Platform

Position Overview

A partner company is seeking a Founding Data Engineer to join their technology team remotely from Germany. This role is a remarkable chance to architect and build the foundational elements of a modern data ecosystem that supports analytics, business intelligence, and upcoming AI projects. The engineer will be responsible for designing and scaling a data platform, influencing architectural decisions, engineering norms, and data methodologies in collaboration with leadership and cross-disciplinary teams.

Key Responsibilities

• Design, develop, and maintain scalable ELT/ETL pipelines integrating data from products, payment gateways, and external APIs.
• Build and oversee cloud data warehouses using platforms like Snowflake, BigQuery, or Redshift.
• Develop and manage data workflow orchestration through Airflow, Prefect, Dagster, or similar tools.
• Optimize data warehouse efficiency including performance, scalability, and cost through robust modeling and query optimization techniques.
• Create maintainable, testable data transformation workflows with dbt or equivalent frameworks.
• Implement comprehensive data quality checks, monitoring, lineage tracking, and documentation procedures.
• Establish secure and privacy-conscious data handling policies, including access management and sensitive data protection.
• Design semantic layers and unified business metrics to support analytics and organizational decision-making.
• Collaborate with Product, Growth, and Engineering teams on analytics, reporting, experimentation, event tracking, and API integrations.
• Champion DataOps practices including CI/CD, version control, automated testing, and documentation standards.
• Contribute to the ongoing evolution of data strategy and foundational technologies for future AI and machine learning efforts.

Qualifications and Experience

• Minimum 3 years’ experience in data engineering or a similar role focused on data systems.
• Advanced proficiency in SQL and Python; Scala knowledge is an advantage.
• Hands-on experience with cloud-based data warehouses such as Snowflake, BigQuery, or Redshift.
• Proven track record with production data pipelines and scalable architectures.
• Experience with orchestration tools including Airflow, Prefect, or Dagster.
• Strong grasp of data modeling and transformation using dbt or comparable tools.
• Competence in implementing data quality, monitoring, governance, and documentation.
• Excellent communication skills to effectively collaborate with diverse teams.
• A strong sense of ownership focused on reliability and maintainability over time.
• Familiarity with secure data handling and privacy-focused practices.

Desired Qualifications

• Experience in B2C SaaS, subscription services, or marketplace business environments.
• Knowledge of product analytics platforms like Segment, Amplitude, or Mixpanel.
• Exposure to creating semantic layers or canonical data models.
• Experience with streaming technologies such as Kafka or Kinesis.
• Involvement with ML infrastructure, feature stores, or AI-centric data systems.
• Previous experience in startup or scale-up environments building data platforms.

Benefits and Work Conditions

• Competitive salary package.
• Fully remote work with flexible hours.
• 22 paid leave days plus local public holidays.
• Opportunity to design and influence a state-of-the-art data platform from inception.
• High degree of ownership and impact on architecture and engineering practices.
• Access to contemporary tools and modern engineering workflows.
• Chance to tackle meaningful technical challenges with business impact.
• A collaborative, product-driven culture where data is central to decision-making.
• Professional growth opportunities in a dynamic tech environment.