We are seeking a Data Engineer to join our team in building and maintaining data infrastructure. The successful candidate will be responsible for designing, building, and maintaining large-scale data systems, including data pipelines, data warehouses, and data lakes.
This is a fully remote opportunity with the potential to become a permanent position. The Data Engineer will work closely with data architects, data scientists, and other stakeholders to ensure that the entire data system meets the needs of the business.
* Design, build, and maintain large-scale data systems.
* Design and implement data warehouses using tools such as Amazon Redshift, Google BigQuery, and Snowflake.
* 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.
* Evaluate data quality and integrity by developing and implementing data validation and data cleansing processes.
Requirements:
* 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
* Strong experience with data warehousing and data lakes
* Strong experience with data validation and data cleansing
* Strong collaboration and communication skills
* Bachelor's degree in Computer Science, Engineering, or a related field
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
* Experience with data governance and data security