Data Engineer

The Data Engineer will be instrumental in building and maintaining robust data pipelines, ensuring the integrity and quality of our data, and contributing significantly to the design and expansion of our data systems. This role is designed for professionals at the mid-level to senior stages of their careers, offering a unique opportunity to directly impact our Engineering department's operations and initiatives through close collaboration and targeted data solutions.

• Develop and Maintain Data Pipelines: Design, build, and manage scalable data pipelines using our ETL system Keboola, ensuring efficient data extraction, transformation, and loading processes.
• Programming: Write and maintain Python scripts for data processing, automation, and integration tasks within the cloud environment.
• Data Querying and Management: Utilize SQL for data querying, management, and optimization to support business intelligence and analytics.
• Operational Support: Provide operational support for data systems, including monitoring and basic troubleshooting.

This role demands a proactive and collaborative approach, with a strong focus on leveraging cloud technologies to drive data-driven decision-making and enhance business outcomes.

What We Look For:

• Deep understanding of SQL, analytical data warehouses (e.g., Snowflake), and hands-on experience with ETL/ELT best practices
• Proficiency in Python, underscored by a track record of deploying high-quality code in production environments
• Familiarity with Git, Jira
• Proven experience in data engineering or a similar role
• Experience in building and maintaining data pipelines
• Good problem-solving skills and attention to detail
• Good communication skills and the ability to work collaboratively with the engineering team and other teams to identify and fulfill data requirements
• Willingness to bring new ideas and learn new technologies

KPI's typical for the position

• Ensuring data availability of all key dimensions and metric across the company reporting
• Ensure the reliability and stability of data flows, minimizing downtime and ensuring data availability for business processes
• Monitoring of the cost-effectiveness of data processing and storage solutions, promoting budget management and cost savings.