Data Engineering Opportunity
We are seeking an experienced Data Engineer to join our team and contribute to the design, development, and maintenance of large-scale data systems.
The successful candidate will be responsible for designing and building data pipelines, data warehouses, and data lakes using tools such as Apache Beam, Apache Spark, and AWS Glue. They will work closely with data architects, data scientists, and other stakeholders to ensure that the entire data system meets the needs of our business.
* Design and implement scalable automated testing solutions using Ruby/Selenium-based frameworks.
* Develop and maintain data pipelines using tools such as Apache Beam, Apache Spark, and AWS Glue.
* Develop and maintain data lakes using tools such as Apache Hadoop, Apache Spark, and Amazon S3.
* Work with data architects to design and implement data models and data architectures.
* Collaborate with data scientists to develop and deploy machine learning models and data products.
* Ensure data quality and integrity by developing and implementing data validation and data cleansing processes.
About the Role
This is a fully remote opportunity with the potential to become a permanent position. The ideal candidate will have 5+ years of experience in data engineering or a related field, including experience with programming languages such as Python, Java, and Scala. They will also have strong experience with data modeling and data architecture, as well as data engineering tools such as Apache Beam, Apache Spark, AWS Glue, Amazon Redshift, Google BigQuery, and Snowflake.
Key Qualifications
* 5+ years of experience in data engineering or a related field.
* 2-4 years of experience in Ruby products, including Ruby on Rails framework.
* 5+ years of experience with programming languages such as Python, Java, and Scala.
* 3+ years of experience with data modeling and data architecture.
* 3+ years of experience with data engineering tools such as Apache Beam, Apache Spark, AWS Glue, Amazon Redshift, Google BigQuery, and Snowflake.
Nice to Have
* Experience with machine learning and data science.
* Experience with cloud-based data platforms such as AWS, GCP, or Azure.
* Experience with containerization using Docker and Kubernetes.
* Experience with agile development methodologies such as Scrum or Kanban.