Data Engineer (Real Estate)

ABOUT THE PROJECT

Within this project, you will develop an IoT platform for a real estate company. The idea of this product is to make smart, AWS-based solutions for managing thermostats, smart locks, and other equipment in our client's apartments, and to make it easy to use. Our globally distributed teams are working on an event-driven system that will allow direct monitoring and control of devices located in apartments in the United States. On the Klika Tech side, we are responsible for the system's end-to-end behavior, including front-end, back-end, and mobile applications.

YOUR ROLE

• Design data models and evolve the overall data architectures;
• Develop, maintain and improve data pipelines and data infrastructure;
• Manage databases and data warehouses to ensure data is accessible and reliable;
• Create dashboards and provide data analysis and reports; 
• Ensure the security and privacy of sensitive data;
• Monitor and optimize the performance of data platforms;
• Write and maintain technical documentation;
• Cooperate with development team and client representatives;
• Convert business requirements into technical requirements;
• Decompose and estimate required functionality;
• Taking part in Agile ceremonies (dailies, planning etc).

REQUIREMENTS

• 5+ years of experience working with data storage technologies such as data lakes, data warehouses and traditional relational and non-relational databases;
• Experience with Snowflake, DBT;
• Experience with Cube.io, Airbyte;
• Knowledge of programming languages such as Python;
• Knowledge of data architecture patterns and data access patterns;
• Experience with cloud computing platforms such as AWS;
• Experience with infrastructure as code tools such as Terraform;
• Knowledge of Git branching models and strategies;
• Knowledge of data modeling, data mapping principles, and best practices;
• Knowledge of OSI model;
• B2+ level of English.

NICE TO HAVE

• 2+ years of experience working with live production systems;
• Notion of machine learning and data science concepts;
• Experience with data visualization tools such as Tableau or Power BI;
• Notion of containerization technologies such as Kubernetes;
• Experience with data streaming technologies such as Apache Flink;
• Knowledge of data governance and compliance regulations.