Data Engineer, Data and Science

• Design, build and maintain core data infrastructure pieces that allow Aircall to support our many data use cases.
• Enhance the data stack, lineage monitoring and alerting to prevent incidents and improve data quality.
• Implement best practices for data management, storage and security to ensure data integrity and compliance with regulations.
• Own the core company data pipeline, responsible for converting business needs to efficient & reliable data pipelines.
• Participate in code reviews to ensure code quality and share knowledge.
• Lead efforts to evaluate and integrate new technologies and tools to enhance our data infrastructure.
• Define and manage evolving data models and data schemas. Manage SLA for data sets that power our company metrics.
• Collaborate with applied scientists, data scientists, analysts and other business stakeholders to drive efficiencies for their work, supporting complex data processing, storage and orchestration

A little more about you:

• Bachelor's degree or higher in Computer Science, Engineering, or a related field.
• 3+ years of experience in data engineering, with a strong focus on designing and building data pipelines and infrastructure.
• Proficient in SQL and Python, with the ability to translate complexity into efficient code.
• Experience with data workflow development and management tools (dbt, Airflow).
• Solid understanding of distributed computing principles and experience with cloud-based data platforms such as AWS, GCP, or Azure.
• Strong analytical and problem-solving skills, with the ability to effectively troubleshoot complex data issues.Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
• Prior experience designing AI-ready data semantic layer is a major plus, specifically for enabling low-latency, high-fidelity analytics at scale.
• Experience with data tooling, data governance, business intelligence and data privacy is a plus.