Data Engineer Opportunity
An exciting opportunity awaits a skilled Data Engineer to contribute to the design, building, and maintenance of data infrastructure.
As a key member of our team, you will be responsible for designing, implementing, and maintaining large-scale data systems, including data pipelines, data warehouses, and data lakes.
You will collaborate with data architects, data scientists, and other stakeholders to ensure that our data systems meet the needs of our business.
This is a fully remote opportunity with the potential to become a permanent position.
Key Responsibilities:
* Data Systems Design: Design, build, and maintain large-scale data systems.
* Data Warehousing: Design and implement data warehouses using tools such as Amazon Redshift, Google BigQuery, and Snowflake.
* Automated Testing: Design and implement scalable automated testing solutions using Ruby/Selenium-based frameworks.
* Data Pipelines: Develop and maintain data pipelines using tools such as Apache Beam, Apache Spark, and AWS Glue.
* Data Lakes: Develop and maintain data lakes using tools such as Apache Hadoop, Apache Spark, and Amazon S3.
* Data Modeling: Work with data architects to design and implement data models and data architectures.
* Collaboration: Collaborate with data scientists to develop and deploy machine learning models and data products.
* Data Quality: Ensure data quality and integrity by developing and implementing data validation and data cleansing processes.
Qualifications:
* Experience: 5+ years of experience in data engineering or a related field.
* Ruby Experience: 2 - 4 years of experience in Ruby products, including Ruby on Rails framework.
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* Data Engineering Tools: 3+ years of experience with data engineering tools such as Apache Beam, Apache Spark, AWS Glue, Amazon Redshift, Google BigQuery, and Snowflake.
* Strong Skills: Strong experience with data warehousing and data lakes, strong experience with data validation and data cleansing, and strong collaboration and communication skills.
* Educational Background: Bachelor's degree in Computer Science, Engineering, or a related field.
Nice to Have:
* Machine Learning Experience: Experience with machine learning and data science.
* Cloud Platforms: Experience with cloud-based data platforms such as AWS, GCP, or Azure.
* Containerization: Experience with containerization using Docker and Kubernetes.
* Agile Methodologies: Experience with agile development methodologies such as Scrum or Kanban.
* Data Governance: Experience with data governance and data security.