Data Engineer Middle (SAP Datasphere, Databricks) in Ajax Systems

Ajax Systems is an international technology company and the largest manufacturer of security systems in Europe. Ajax products are already trusted by more than 4.5 million end users and 330 thousand PRO users in more than 180 countries. The company offers comprehensive solutions for the protection of residential and commercial facilities of various sizes. Currently, the Ajax portfolio includes 280 devices for intrusion protection, video surveillance, fire safety, and comfort and automation. Every year we show multiple growth in both the team size and the number of users worldwide.

Ajax Systems has full-cycle manufacturing: from idea generation and prototyping to mass production and sales worldwide. Each department covers a certain operational need of the business in full. The company's specialists are involved at all stages: from the production line in Ukraine to the logistics center in Poland, from where the products are sent to distributors around the world.

Middle Data Engineer is responsible for the development, support and optimization of data processing flows and solutions under the leadership of the Senior Data Engineer (Lead). The main goal is to provide reliable, high-quality and scalable data for analytics, machine learning and business applications. 

Key areas of work:

• Implementation of ETL/ELT processes and management of data flows.
• Structuring, cleaning and consolidation of data from various sources.
• Supporting the deployment and administration of Data Warehouse and Data Lake solutions on SAP Datasphere and Databricks.
• Ensuring the quality, accuracy and reliability of data in accordance with corporate standards and management policies
• Collaborate with Senior Data Engineer and other team members to implement the full cycle of data processing.

Requirements:

• Higher degree in IT, Data Science, Computer Science or related fields.
• 2-5 years of experience as a Data Engineer or related roles.
• Knowledge of SAP Datasphere and/or Databricks mandatory.
• Proficiency in SQL, Python/Scala, Spark.
• Experience in developing ETL/ELT processes and data flows.
• Understanding the concepts of Data Warehousing, Data Lake and basic principles of Data Governance.
• Knowledge of data security principles and compliance requirements (GDPR, local regulations) preferred.
• Analytical thinking and problem solving skills.
• Ability to work in a team under the leadership of Senior Data Engineer.

Responsibilities:

• Development, support and optimization of ETL/ELT flows for structured and unstructured data.
• Cleaning, transformation and consolidation of data according to technical requirements.
• Support deployment and administration of Data Warehouse and Data Lake solutions on SAP Datasphere and Databricks.
• Monitoring and ensuring data quality, consistency and reliability.
• Collaboration with Senior Data Engineer to implement best practices and corporate data processing standards.
• Preparation of data for analytics, reporting and machine learning.
• Documentation of data flows, processes and