About Us
We're a world-leading smart mobility SaaS tech company with almost 2,300,000 active users. Our teams are collaborative, vibrant, and fast-growing, and all team members are empowered with the freedom to influence our products and technology.
Are you curious, innovative, and passionate? Do you take ownership, embrace challenges, and love problem-solving?
We are looking for a Senior Data Engineer who will help us build robust pipelines and infrastructure to process and analyze audio and video data, revolutionizing the way our customers use connected technology.
Your Role
- Design, build, and maintain data pipelines and ETL workflows using tools like Airflow .
- Develop monitoring systems to detect upstream data changes and maintain data freshness.
- Optimize relational and analytical databases for performance, including partitioning, indexing, and table design .
- Implement data quality , data lineage , and source documentation standards.
- Manage and tune analytics databases such as ClickHouse, Druid, StarRocks, or Doris .
- Work with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle .
- Leverage distributed query tools (e.g., Spark , Trino ) to support scalable data analysis.
- Build, deploy, and monitor services in Linux environments , including shell scripting and debugging.
- Create and maintain Docker images , ensuring consistent environments for development and deployment.
- Integrate data workflows with CI / CD pipelines using tools such as GitLab, GitHub, or Bitbucket .
Your Qualifications
Core Technical Skills
Strong proficiency in one or more of the following : C, C++, C#, Go, or Rust .Proficiency in Python for scripting and automation.Experience with Airflow and complex ETL processes involving large datasets.Solid understanding of data architecture, database optimization , and monitoring best practices.Hands-on experience with Docker , Linux environments , and version control systems .Preferred / Nice-to-Have Skills
Experience or interest in Kubernetes and Helm charts .Familiarity with AI / LLM data pipelines — generating tables and views optimized for low-latency queries .Experience with LLM Agent development , RAG workflows , or related frameworks such as LlamaIndex , LangGraph , or FastAPI .Knowledge of stream processing systems to accelerate data ingestion into analytics databases.Exposure to feature engineering and table design in collaboration with data scientists.Qualifications & Experience
Bachelor’s Degree or Advanced Diploma in Computer Science, Information Technology, or Engineering , with 3–5 years of experience in a software or technology environment focused on data systems architecture, deployment, and monitoring.Candidates without a degree must have 6–10 years of equivalent experience in data engineering, infrastructure management, or backend systems development.