Jobgether
Data Engineer, Product
TLDR
Own end-to-end data pipelines powering ML-driven product development, personalization, and recommendations at scale.
Accountabilities:
- Design, build, and maintain scalable ETL/ELT data pipelines that transform raw data into high-quality datasets for machine learning and product use cases.
- Develop and optimize data transformation workflows supporting feature engineering for both offline model training and online inference systems.
- Collaborate closely with ML Engineers to understand data requirements and deliver reliable inputs for recommendation systems and predictive models.
- Ensure strong data quality, governance, and monitoring across all pipelines to guarantee accuracy, reliability, and consistency of datasets.
- Own data pipelines end-to-end, including design, implementation, deployment, monitoring, and continuous improvement.
- Improve performance, scalability, and efficiency of large-scale data processing systems, including batch and near real-time workloads.
- Contribute to building robust data foundations that enable experimentation, personalization, and ML-driven product innovation.
- 5+ years of experience in Data Engineering or a similar role within data-intensive or product-driven environments.
- Strong hands-on experience with Apache Spark and Python for large-scale data processing and transformation.
- Solid knowledge of SQL and experience designing and working with data models and transformation logic.
- Proven experience building and maintaining ETL/ELT pipelines with end-to-end ownership.
- Experience working with high-volume data systems, including batch and/or near real-time processing pipelines.
- Strong ability to collaborate with Machine Learning and product teams in ML-driven environments.
- Familiarity with Databricks is a plus.
- Experience with streaming technologies (e.g., Kafka, Flink), feature stores, or ML data workflows is highly desirable.
- Strong problem-solving mindset with attention to scalability, performance, and data reliability.
- Competitive salary aligned with senior data engineering market standards (€64,800–€74,400 annually referenced in original posting)
- Employee stock option program
- Performance-based bonuses and referral rewards
- Flexible remote-first working model with location autonomy
- Personal learning and professional development budget
- Additional paid leave options
- Paid volunteering opportunities
- Opportunity to work remotely while traveling
- High-growth environment focused on product innovation and ML-driven systems
Requirements:
Benefits:
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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Benefits
Learning Budget
Personal learning and professional development budget
Focus on product innovation and ML systems
High-growth environment focused on product innovation and ML-driven systems
Paid Time Off
Paid volunteering opportunities
Remote-Friendly
Opportunity to work remotely while traveling
Stock Options
Employee stock option program
Jobgether runs the largest remote job platform, effectively linking job seekers with over 200,000 flexible and remote opportunities that match their unique skills and preferences. Our focus is on enhancing the hiring process, ensuring efficiency while prioritizing the candidate experience, particularly in the growing health and wellness sector.
- Founded
- Founded 2020
- Employees
- 11-50 employees
- Industry
- Professional Services
Data Engineer