Data Engineer Position
We are seeking a highly skilled Data Engineer to join our team and contribute to the design, building, and maintenance of large-scale data systems.
As a key member of our team, you will be responsible for designing, implementing, and maintaining data pipelines, data warehouses, and data lakes using various tools such as Apache Beam, Apache Spark, and AWS Glue.
You will work closely with data architects, data scientists, and other stakeholders to ensure that the entire data system meets the needs of our business.
This is a fully remote opportunity with the potential to become a permanent position.
Key Responsibilities:
* Data System Design and Implementation: Design and implement large-scale data systems, including data pipelines, data warehouses, and data lakes.
* Data Warehouse Development: Design and implement data warehouses using tools such as Amazon Redshift, Google BigQuery, and Snowflake.
* Automated Testing Solutions: Design and implement scalable automated testing solutions using Ruby/Selenium-based frameworks.
* Data Pipeline Development: Develop and maintain data pipelines using tools such as Apache Beam, Apache Spark, and AWS Glue.
* Data Lake Development: Develop and maintain data lakes using tools such as Apache Hadoop, Apache Spark, and Amazon S3.
Qualifications:
* Experience in Data Engineering: 5+ years of experience in data engineering or a related field.
* Programming Language Skills: Strong skills in programming languages such as Python, Java, and Scala.
* Data Modeling and Architecture: 3+ years of experience with data modeling and data architecture.
* Data Engineering Tools: Strong experience with data engineering tools such as Apache Beam, Apache Spark, AWS Glue, Amazon Redshift, Google BigQuery, and Snowflake.
* Collaboration and Communication Skills: Strong collaboration and communication skills.
* Degree Requirement: 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-Based Data Platforms: Experience with cloud-based data platforms such as AWS, GCP, or Azure.
* Containerization: Experience with containerization using Docker and Kubernetes.
* Agile Development Methodologies: Experience with agile development methodologies such as Scrum or Kanban.