Data Engineer/ Architect

In this position, you will serve as the critical bridge between our data organization and DevOps teams, tackling complex challenges around data optimization, large-scale architecture, and high-performance systems. About the Role: Our data landscape is vast and continually evolving. The ideal candidate has extensive experience designing, optimizing, and operating advanced data systems—particularly dealing with complex query optimization and large-scale data flows. While this is not a formal managerial role, it does require strong leadership abilities, including: Guiding cross-functional data initiatives Collaborating closely with DevOps to ensure seamless data operations Demonstrating a proven track record in managing large, high-performing data environments and overseeing the end-to-end execution of complex data architecture projects If you thrive in a fast-paced environment where you can drive innovation, optimize data systems, and mentor others technically—without necessarily being the formal “head of the team”—we want to hear from you. What We Value: Proven Experience in Large-Scale Data Management: Comfort with big data frameworks, data pipeline orchestration, and performance tuning. Technical Versatility: Ability to work across various databases, data streaming platforms, and programming languages (TypeScript/Python/Java). Open-Ended Problem Solving: Demonstrated success in tackling ambiguous or complex data challenges. Open Source Mindset: Comfort and familiarity with open-source tools and platforms. Detail-Oriented: Strong emphasis on data accuracy, best practices, and thorough testing. Self-Driven & Autodidactic: Ability to learn new tools, technologies, and methodologies on the fly. Effective Communication: Strong verbal and written communication skills; English at a mother-tongue level is required. Requirements & Technologies: Below are some of the technologies we use. Direct experience with each is not mandatory, but you should be comfortable adopting new tools within these categories: Databases & Streaming: SQL, MongoDB, Redis, PubSub, ClickHouse, Elasticsearch, BigQuery Data Pipeline Tools: Airflow, Luigi, Azkaban, dbt Languages: TypeScript, Python, Java Infrastructure: Cloud platforms (e.g., GCP), CI/CD, Git & GitHub, Kubernetes (in coordination with DevOps)