We are seeking a highly skilled Data Engineer to design, build and maintain large-scale data systems.
This exciting opportunity will enable you to work closely with data architects, data scientists and other stakeholders to ensure that the entire data systems meet the needs of our business.
This is a fully remote opportunity with the potential to become a permanent position.
Key Responsibilities
* 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
* Ensure data quality and integrity by developing and implementing data validation and data cleansing processes
* Collaborate with other teams to ensure that data systems meet the business's needs
* Stay up-to-date with new technologies and trends in data engineering and make recommendations for adoption
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
* 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