Senior Python Engineer
J
JobgetherData Engineering
Based in Germany, European time zonesFull-TimeSenior
Salary5,000 - 6,500 USD per month
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Job Details
- Required Skills
- PostgreSQLPythonSQLKafkaNumpyRabbitmqRedisPandasscikit-learnDistributed Systems
Requirements
- Strong professional experience developing backend systems with advanced Python and SQL.
- Experience working with large-scale data processing, distributed systems, and high-load environments.
- Knowledge of event-driven architectures and message queue technologies such as RabbitMQ or Kafka.
- Ability to investigate technical challenges, analyze data, and make informed engineering decisions.
- Experience building reliable, maintainable software with a strong focus on quality and scalability.
- Strong ownership mindset with the ability to manage projects independently and deliver impactful solutions.
- Excellent communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Comfortable working in a fast-paced environment with changing priorities and evolving requirements.
- Experience with data products, Big Data environments, BI, analytics, or machine learning teams is considered an advantage.
- Familiarity with technologies such as PostgreSQL, Redis, Puppeteer, Playwright, Selenium, Pandas, NumPy, or Scikit-learn is a plus.
Responsibilities
- Develop and maintain robust Python-based solutions for large-scale data ingestion and backend systems.
- Build, improve, and maintain data collection processes, including web scrapers and automated data pipelines.
- Enhance platform performance, reliability, observability, and overall data quality.
- Conduct technical research and investigations to solve complex engineering challenges.
- Take ownership of architectural and conceptual components, including reliability, quality assurance processes, and automation initiatives.
- Collaborate with engineering teams through code reviews, technical discussions, and cross-functional initiatives.
- Analyze existing systems, reduce technical debt, and improve codebase maintainability.
- Make data-driven technical decisions through exploratory data analysis and evaluation of system performance.
- Contribute to scalable solutions using modern backend technologies, distributed systems, and event-driven architectures.
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