Data Engineer

💰 Salary discussed after interview / month

📍 Место работы Тбилиси

Published: 15 May 2026 Updated: 9 hours ago

📝 Description

📌 Responsibilities
— Build scalable, global, complex systems to solve problems using high-quality software;
— Develop and implement quality controls and standards to ensure trust in data;
— Develop reusable API sets for use across various business units;
— Process data using the most productive and efficient practices to turn data into insights;
— Experiment with new technologies to improve the platform;
— Maintain sufficient documentation to ensure business continuity;
— Work with the team to achieve shared goals;
— Explain data from a business perspective and communicate clearly and effectively with business partners of varying technical levels;
— Willingness to learn and adapt.
📌 Requirements
— At least 2 years of experience as a Data Engineer;
— Higher education in Computer Science or Information Technology;
— Ability to write high-performance, high-quality code in Python or other equivalent languages such as Node, Java, Go, Scala, with the ability to adapt;
— Knowledge of computer science fundamentals such as object-oriented design, algorithm design, data structures, problem solving, and complexity analysis;
— Strong SQL skills;
— Good understanding of different types of storage/databases and their purposes;
— Self-motivated, fast learner, detail-oriented, team player with a sense of humor;
— English level: Intermediate or higher.
📌 We offer
— Working conditions: you can work fully remotely, from the office, or choose a hybrid option;
— Active corporate life (parties / pizza days / PlayStation / fruit / coffee / snacks / movies);
— English language courses;
— Private health insurance and reimbursement of sports activities.
Nice-to-have skills:
- Experience working with distributed, multi-tier systems, algorithms, and relational / non-relational databases;
- Experience with data workflow management tools: Airflow, Google DataFlow;
- Experience with various software development lifecycle frameworks such as Docker, Kubernetes, Jenkins, Vault;
- Experience with cloud solutions such as Google Cloud Platform, Qubole, Segment, Tableau, Workato;
- Good understanding of concepts and approaches to real-time direct data ingestion;
- Experience with cloud environments such as AWS and container orchestration platforms such as Kubernetes.