Data Infrastructure Engineer

At Divar, we're at the forefront of technological innovation, providing cutting-edge solutions that empower business to thrive in today's digital landscape. As a rapidly growing tech company, we're looking for a talented and motivated Data Infrastructure Engineer to join our dynamic Infrastructure team. If you are passionate about building robust data systems and want to contribute to transformative projects, and excited about the opportunity to join a forward-thinking company and contribute to building data infrastructure that drives success we'd love to hear from you.

Position Summary 

We are seeking a highly skilled Data Infrastructure Engineer to design, build, and maintain the scalable data infrastructure that powers our business intelligence and other data-driven operations. As a key member of our Infrastructure team, you will work closely with data scientists, data analysts, and other engineers to ensure seamless data integration and delivery.

Responsibilities 

• Design, implement, and manage high-performance data pipelines and data architectures, ensuring efficient data flow and processing.
• Develop, test, and optimize ETL (Extract, Transform, Load) processes to support data warehouse solutions and maintain data integrity.
• Collaborate with cross-functional teams to understand and address data infrastructure needs, supporting self-service analytics and other data services.
• Monitor and troubleshoot data infrastructure for performance, security, and reliability.
• Implement best practices for data governance, data quality, and data security across the data lifecycle.
• Stay up-to-date with emerging trends and technologies in data engineering and infrastructure to continually improve and innovate.
• Enable robust development environments, both in the cloud and on-premise, to support data analysis, data processing, and the training of deep learning models.
• Facilitate the integration and usage of third-party deep learning models (e.g. OpenAI). 
   

• Bachelor's degree in Computer Science, Information Technology, or a related field. Master's degree preferred.
• Proven experience as a Data Infrastructure Engineer,  Infrastructure Engineer, Data Engineer, MLOps Engineer or a similar role.
• Strong proficiency in SQL and experience with relational databases such as PostgreSQL, ClickHouse or others.
• Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, or Flink.
• Knowledge of ETL tools and processes (e.g., Airflow).
• Proficient in languages such as Python, Java, or Scala.
• Expertise in containerization and orchestration technologies, including Kubernetes and Docker.
• Familiarity with MLOps practices and tools to streamline the deployment and management of machine learning models.
• Understanding of how large language models (LLMs) are utilized and the underlying mechanisms that enable their functionality.
• Experience in setting up, maintaining, integrating, and customizing open-source data tools (e.g. Airflow, JupyterHub, Coder, Open Metadata, …)
• Understanding of data governance and data security best practices.
• Excellent problem-solving skills and a proactive approach to dealing with technical challenges.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.
   

• Flexible working hours.
• A dynamic working environment with a culture that is open, innovative and performance oriented.
• Supplementary health insurance.
• Various on-site entertainments.
• Competitive salary package.