Lead Data Engineer

at  Nordhealth

WHO ARE WE?

Nordhealth’s mission is to build software that improves the daily lives of healthcare professionals. We build software that empowers veterinary and therapy professionals to provide the best possible care experiences to their patients. Our products are used daily by over 55,000 professionals in clinics and hospitals across 30+ countries. We excel with 20+ years of experience in healthcare and veterinary software.
We understand that talent comes from everywhere and anywhere. The greater our diversity, the better the products we deliver. That’s why we are a remote-first company, headquartered in Helsinki, Finland, with all ~400 employees working either remotely or from collaboration hubs. While our market presence is currently strongest in the Nordics, our customer base is rapidly growing in our other markets too, especially in Europe and North America (more at our website nordhealth.com.)
Creating great products is at our very core, but it’s the people who make companies great, not the other way around. We spend more time with our co-workers than anyone else in our lives. Being part of an exceptional team is not only important for your personal mindfulness but key for your professional progression.

Qualifications:

• 7+ years of experience in data engineering, with a strong background in building and managing data pipelines and architectures.
• Strong knowledge of SQL and experience with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra).
• Familiarity with data warehousing solutions such as Amazon Redshift, Google BigQuery, or Snowflake.
• Experience with data orchestration tools like Apache Airflow or similar.
• Knowledge of data modeling, ETL/ELT processes, and data warehousing concepts.
• Strong problem-solving skills and the ability to troubleshoot complex data issues.
• Proficiency in programming languages such as Python
• Extensive experience with data processing frameworks such as Apache Spark, Flink, or similar technologies

Preferred Qualifications:

• Experience with real-time data processing and stream processing frameworks.
• Knowledge of data governance and data security best practices.
• Familiarity with big data technologies such as Hadoop, Hive, or similar.
• Certification in cloud data engineering (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer) is a plus

We are looking for a Staff/Lead Data Engineer to partner with our Reporting Product Manager and collaborate with data analysts and other stakeholders to understand Provet clouds data requirements and deliver a high-quality vision for Data at Provet cloud. Reporting into the Director of Engineering, you’ll help shape and deliver the direction our solution takes in the future, ensuring at all times it meets the needs of our business and is scalable into the future.

Key Responsibilities:

• Design, develop, and maintain scalable and efficient data pipelines to process large volumes of data from various sources.
• Develop a management and governance process for our Datamodels and data pipelines
• Architect and implement robust data storage solutions that support real-time and batch data processing.
• Break down complex concepts into understandable pieces of information.
• Willingness to whiteboard, virtually or in person when possible, to tease out a problem
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality data solutions.
• Optimise and tune data pipelines for performance, reliability, and scalability.
• Implement data quality and validation checks to ensure data integrity and consistency.
• Develop and maintain documentation for data engineering processes and systems.

Qualifications:

• 7+ years of experience in data engineering, with a strong background in building and managing data pipelines and architectures.
• Strong knowledge of SQL and experience with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra).
• Familiarity with data warehousing solutions such as Amazon Redshift, Google BigQuery, or Snowflake.
• Experience with data orchestration tools like Apache Airflow or similar.
• Knowledge of data modeling, ETL/ELT processes, and data warehousing concepts.
• Strong problem-solving skills and the ability to troubleshoot complex data issues.
• Proficiency in programming languages such as Python
• Extensive experience with data processing frameworks such as Apache Spark, Flink, or similar technologies.

Preferred Qualifications:

• Experience with real-time data processing and stream processing frameworks.
• Knowledge of data governance and data security best practices.
• Familiarity with big data technologies such as Hadoop, Hive, or similar.
• Certification in cloud data engineering (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer) is a plus.