Data Engineer at Appsilon responsible for building scalable data pipelines and ensuring data quality for global organizations. Collaborate with cross-functional teams to leverage massive datasets.
Responsibilities
Design, build, and maintain scalable data pipelines across diverse environments
Integrate data from multiple internal and external sources into data warehouses or data lakes
Collaborate closely with Data Scientists, ML Engineers, and Developers to ensure data quality, structure, and availability
Monitor and improve data integrity, performance, and reliability
Build and optimize database schemas, data models, and documentation
Implement data governance, security best practices, and compliance standards
Requirements
Backend Python Development
Strong experience building scalable backend systems in Python
Comfortable with modern language features (type hints, decorators, generators)
Able to design clean, maintainable APIs using FastAPI, Django REST Framework, or Flask
Good understanding of performance optimization and Python internals
A collaborative mindset — you enjoy working closely with cross-functional teams
Data Engineering
Hands-on experience designing and operating ETL/ELT pipelines
Solid SQL skills and ability to model, optimize, and maintain database structures
Experience integrating data from multiple sources (databases, APIs, streaming)
Familiarity with large-scale data processing tools or distributed systems
Nice to have: Experience with cloud platforms (AWS/Azure/GCP)
Knowledge of R
Experience with Docker, Kubernetes, and CI/CD tools (GitHub Actions, GitLab CI)
Understanding of data governance, metadata management, and security
Experience in life sciences, biotech, genomics, or enterprise data environments
Prior remote work experience with international teams
Life science skills: Molecular Biology & Bioinformatics, Clinical Trials - Data Tools & Flow, CDISC & Clinical Data Standards, Nextflow
Benefits
Competitive B2B compensation with clear salary ranges (up to 23.000 PLN net B2B)
Modern equipment (MacBook / ThinkPad + Linux environment)
Budget for professional development (certifications, courses, conferences)
Opportunity to collaborate with industry experts on innovative data products
A supportive, ambitious, and friendly team that cares about excellence
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