Sobre este puesto de Data Engineer en Oxylabs
The team waiting for you:
As our Data Engineer, you will be responsible for tackling a diverse and challenging range of problems to help us make better business decisions at Oxylabs.io. In this role, you will focus on making data (internal/external, structured/unstructured, batch/real-time, etc.) accessible across Oxylabs.io while ensuring its accuracy and timeliness. You will design, build, and maintain data pipelines, and you’ll also have the opportunity to develop various internal tools. This is an excellent opportunity for an analytical thinker who thrives in a fast-paced environment, enjoys hands-on technical work, and is eager to learn new technologies.
In this role, you will:
Architect and maintain robust data models by conducting thorough analysis of our complex data ecosystem to define clear relationships between data sources.
Engineer and optimize scalable, high-performance data pipelines using Google Cloud Platform and Airflow.
Translate complex business logic into efficient transformations while maintaining rigorous standards for data quality and system reliability.
Develop internal applications, automations, and reverse ETLs using Python.
Collaborate with cross-functional teams to identify automation opportunities and translate business challenges into scalable technical solutions.
Your skills & experiences:
Proficiency in at least one programming language, ideally Python.
Experience with cloud infrastructure (ideally Google Cloud or AWS).
Knowledge of best DataOps practices and tools including version control systems (e.g., Git), Terraform, Docker, Kubernetes, and CI/CD.
Excellent SQL knowledge and understanding of data modelling/data warehousing principles.
Structured mindset approach to problem solving, clear and concise communication, high degree of ownership, keen eye for detail and troubleshooting.
Fluency in English and Lithuanian, written and spoken.
Nice to have:
Familiarity with agent frameworks (e.g., LangChain, Claude Agent SDK, Google ADK) or workflow automation tools (e.g., n8n.io).
Experience with event streaming platforms, such as Kafka or Redpanda.
Proficiency in ClickHouse and other OLAP databases.
A technical aptitude and comfort with engineering-related discussions.
