Data Engineer II

• Bachelor's degree in Computer Science or related field or equivalent experience

• 5+ year of professional experience in data engineering

• Expertise in SQL, databases (MySQL / Redshift / Athena), Data modeling

• Workflow orchestrators (Dagster, Airflow, Prefect)

• Experience working with Python

• Strong communication skills both in person and via virtual mediums

• ETL/ELT design patterns

• Experience with high volume distributed data processing in Spark

• Experience with AWS cloud services

• Background check required

Nice to have:

• Experience with large-scale aggregation and geospatial data (H3 / Quadkey/S2), or with multi-source data integration, is a plus

Compensation Range

Ookla provides a range for the base pay. Factors that may be used to determine your actual pay may include your specific job related knowledge, skills, experience, and geographic location. The salary compensation for this role is 50,000 to 74,000 EUR annually. Individual pay within the compensation range for this business unit specific role is determined based on a variety of factors including experience, scope of the role, capabilities to perform the role, education and training, as well as business and company performance.

The Opportunity:

We're looking for a mid level Data Engineer to join the Ookla Data Engineering team and help us process the world's best collection of data on mobile and fixed internet performance. As a data engineer you will be focused on developing jobs, libraries and operations to support data scientists and analysts as they discover new and exciting ways to apply our data. Applicants should have a strong, data-focused programming background and be passionate about accuracy and performance. You will work on big data using the latest technologies.

• Design and develop high volume data processing pipelines across various platforms including Redshift, Athena, Iceberg, Spark and Airflow

• Implement monitoring, alerting, and data quality checks to ensure pipeline reliability and data accuracy

• Contribute to architectural decisions and technical design discussions for new data platform initiatives

• Participate in code reviews and contribute to team standards for data quality, testing, and documentation

• Support and collaborate with data scientists, analysts, product managers and integrating teams