[Hiring] Data Engineer @Nordhealth

Role Description

The Data Engineer works as part of the Data Engineering team of the Veterinary business unit. This position is responsible for building and maintaining the data infrastructure that supports our internal products. This role involves collaborating closely with Product Managers and Designers to understand requirements and translate them into effective data warehousing solutions. The Data Engineer will also work with Development teams to establish and enforce best practices for data processing and modeling. This role is essential for ensuring data accuracy, efficiency, and scalability, ultimately impacting client retention and satisfaction.

• Design, build, and maintain scalable and reliable data pipelines using Python, PySpark, and SQL.
• Develop and optimize data transformations and ETL processes, ensuring data accuracy and relevance for our clients.
• Collaborate with Product Managers and Designers to understand data requirements and deliver effective solutions that meet client needs.
• Build scalable and discoverable data models in SQL and maintain detailed documentation for each.
• Implement data quality checks and monitoring to ensure data accuracy and integrity, directly impacting the quality of data our clients receive.
• Optimize data storage and retrieval for performance and cost efficiency, considering the demands of client access and reporting.
• Contribute to cluster optimization and maintenance, ensuring efficient resource utilization.
• Document data engineering processes and best practices, with a focus on clear communication for both internal teams and, where appropriate, client-facing documentation.
• Collaborate in continuously improving the team’s working practices and development processes.
• Annual OKRs will be set at the individual level to contribute to the OKRs of the Business unit, Team and the Company.

Qualifications

• At least 2-4 years of experience in a Data Engineering role.
• Proficiency in Python (core + dataframes), with a focus on Object-Oriented Programming and modularity.
• Experience with PySpark for large-scale data processing.
• Solid SQL skills, including the ability to write complex queries and quality checks.
• Proven experience in data modeling and query optimization.
• Experience with DBT is required; experience with Databricks is a big plus.
• Experience with databases like ClickHouse is a big plus.
• Experience with data visualization tools (e.g., Tableau, PowerBI, Looker) is a plus, especially if used for client-facing reporting or dashboards.
• Knowledge of DevOps principles, CI/CD practices, and security is an advantage.
• Full proficiency in English, written and spoken.

Requirements

• Solid professional experience in data engineering, preferably within a fast-growing, global SaaS company supporting client-facing data products.
• Courage to make conclusions, do research, and take ownership.
• Creativity, independent thinking, and proactiveness in problem solving.
• Close cooperation with the team and other stakeholders.
• Capability to work under pressure with tight time schedules.
• Ability to prioritize work tasks and time management both independently and in collaboration with the team.
• Enjoying collaboration with product, design, and other engineers to ensure high-quality implementation.

Benefits

• The chance to work in a meaningful industry and in a fast-growing, global company on a path to changing digital healthcare.
• Competitive compensation and benefits.
• Learning and professional growth opportunities.
• The tools you need, and enjoy using.
• Frequent company events and talented colleagues from around the world.