Data Engineer

Nordhealth

1d•Remote

About The Position

The Data Engineer works as part of the Data Engineering team. 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.

Requirements

Solid professional experience in data engineering, preferably within an area of internal, financial and operational reporting
Courage to make conclusions, do our own research and take ownership is a key to being successful in the role.
Creativity, independent thinking and proactiveness in problem solving are essential success factors for this role.
Close co-operation with the team and with other stakeholders is required.
Independence in connecting with relevant parties and good collaboration skills are required in this role.
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.
2-4 years of experience in Data Engineering role
Proficiency in Python (core + dataframes). 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
Full proficiency in English, written and spoken.

Nice To Haves

Ideally, you have already gained some experience from working in a fast growing, global SaaS company.
Experience with Databricks and DBT is a big plus.
Experience with databases like ClickHouse is a big plus.
AI fluency (MCP, agents, cross-agents review)
Knowledge of DevOps principles and CI/CD practices is an advantage.

Responsibilities

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 internal reporting.
Collaborate with Leadership Team 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.
Collaborating 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.