preply - Senior II - Back-End Engineer
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT
Requirements
• Exposure to architectural patterns of a large, high-scale web application (e.g., well-designed APIs, high-volume data pipelines, efficient algorithms); • Proven experience leading complex, ambiguous, or greenfield projects end-to-end • Strong communication and cross-functional collaboration skills (English level B2+) • Willingness to be on-call for your squad (1 week every 5 weeks). • Side projects or product ownership experience. • Experience designing systems for marketing attribution, experimentation platforms, or recommendation engines. • Familiarity with cloud platforms (AWS/GCP) and modern DevOps practices. • Familiarity and willing to support small JS/TS tasks when needed.
Responsibilities
• Own and drive technical vision across squads • Develop and own backend features using Python/Django, supporting the creation of new backend services as well as design, create, and/or troubleshoot integrations with third-party vendors. • Scope and lead cross-functional initiatives involving design, data, product, security, and other engineering teams. • Design and implement scalable backend systems, data pipelines, and integrations with third-party platforms • Mentor and coach junior and middle engineers across squads • Improve performance, tracking, monitoring, and reliability of our systems with an eye on long-term scalability. • Collaborate closely with PMs, EMs, designers, and analysts to make data-informed, user-centered decisions. • Champion engineering best practices: test automation, documentation, observability, and quality-first culture.
Benefits
• Ownership over technical vision for backend services. • Development ownership in Python/Django framework using Django ORM features like QuerySets and Manager API to build new backends as well as integrations with third parties via APIs such as REST, GraphQL or WebSocket protocols (e.g., HTTP requests). • Leadership of cross-functional initiatives involving design, data, product, security teams for backend systems development using Python/Django framework and tools like Docker to containerize applications ensuring scalability across different environments such as Kubernetes clusters with Helm charts or Terraform scripts. • Mentorship opportunities in technical areas including but not limited to software architecture design patterns (e.g., MVC, CQRS), database normalization techniques using SQLAlch0me ORM library for efficient data access and manipulation within Python/Django framework; security best practices such as OAuth2 authentication flow implementation with JWT tokens generation via PyJWT package or OpenID Connect protocols integration into our backend services. • Performance optimization tasks including profiling tools like cProfile module in Python standard libraries to identify bottlenecks and optimize code execution times using techniques like memoization, caching results of expensive function calls; tracking metrics with Prometheus for monitoring system health statuses such as CPU usage percentages or memory consumption levels. • Improving reliability through implementing fault tolerance mechanisms including circuit breakers pattern via Python library called "pybreaker" which helps prevent cascading failures across distributed systems by detecting errors early on before they propagate throughout the system; using retry strategies with exponential backoff algorithms implemented in libraries like tenacity or aiohttp_retry for handling transient network issues when communicating over HTTP/HTTPS protocols between client-server interactions. • Access to professional development resources such as online courses, books and conferences related specifically towards backend engineering topics including but not limited too advanced concepts of distributed systems design principles like CAP theorem or consensus algorithms used in blockchain technologies; Python programming language best practices guides from official documentation pages provided by PEP 8 style guide for maintainable code writing standards. • Opportunities to work on cutting edge projects involving AI and machine learning techniques using libraries such as TensorFlow, PyTorch or Scikit-learn which can be applied towards improving our product offerings through personalized tutor recommendations based upon learner's interests/preferences; natural language processing algorithms for sentiment analysis of user feedback data collected via surveys conducted regularly with learners and tutors alike. • Competitive salary package commensurate to experience level, performance bonuses tied directly towards individual contributions made by team members in terms improving overall product quality or increasing revenue streams; comprehensive benefits including health insurance coverage options available through our partnered
No credit card. Takes 10 seconds.