Ookla
Posted 59 days agoVerified live 1d ago
Data Engineer
Brief overview
Remote
UndergradOr in progress
$85k–$125k/yrStated range
1+ yrsMinimum
SQLMySQLAmazon RedshiftAmazon AthenaData modelingDagsterApache AirflowPrefectPythonETL design patternsELT design patternsAWS cloud servicesApache Spark
About the company
Ooklaookla.com
Ookla is the global leader in internet testing, data and analysis.
Job description
Summary
Ookla is a global leader in connectivity intelligence, seeking an entry level Data Engineer to join their Data Engineering team. The role focuses on developing jobs and operations to support data scientists and analysts, while working with big data technologies.
Responsibilities
- Develop high volume data processing jobs across various platforms including Redshift, Athena, Iceberg, Spark and Airflow
- Debug queries, monitor jobs, identify bottlenecks in system performance and improve efficiency
- Support and collaborate with data scientists, analysts, and product managers
Skills
- Bachelor's degree in Computer Science or related field or equivalent experience
- 1+ year of professional experience in data engineering
- Knowledge of 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
- Background check required
- ETL/ELT design patterns
- Experience with AWS cloud services
- Experience with high volume distributed data processing in Spark
Qualifications
Must Haves
- Bachelor's degree in Computer Science or related field or equivalent experience
- 1+ year of professional experience in data engineering
- Knowledge of 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
- Background check required
Nice to Haves
- ETL/ELT design patterns
- Experience with AWS cloud services
- Experience with high volume distributed data processing in Spark
