AWS Databricks Cloud Data Engineer - Remote - 1960

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Written by AI from the job title and company, not by Cyrten, so some details may not match this job. The employer's own page has the real description.

Position Overview

The AWS Databricks Cloud Data Engineer at Cyrten will be responsible for designing, developing, and maintaining data processing pipelines on the Databricks platform. This remote role requires collaborating with data scientists and business analysts to understand data needs and implement solutions that leverage Databricks and AWS services. The successful candidate will ensure the seamless integration of data sources, optimize data workflows for performance, and maintain data quality standards across multiple databases.

Job Responsibilities

• Design, implement, and maintain robust data pipelines using Databricks and AWS.
• Optimize data ingestion and transformation processes for performance and reliability.
• Collaborate with cross-functional teams to gather requirements and translate them into technical specifications.
• Ensure data accuracy and consistency across various data sources and analytics platforms.
• Monitor and troubleshoot data processing tasks to resolve issues promptly.
• Perform quality checks and validations on datasets to maintain data integrity.
• Document data engineering processes and architectures for knowledge sharing.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 3+ years of experience in data engineering or a related field.
• Proficient in AWS services, particularly S3, Glue, Redshift, and Lambda.
• Hands-on experience with Databricks and Spark for data processing.
• Strong programming skills in languages such as Python, SQL, and Scala.
• Excellent understanding of data modeling and database design.
• Experience with ETL tools and data pipeline orchestration.
• Familiarity with Agile methodologies and version control systems (e.g., Git).

Technologies & Tools

The AWS Databricks Cloud Data Engineer will be utilizing a range of technologies and tools, including but not limited to:

• AWS (Amazon Web Services) for cloud infrastructure.
• Databricks for data engineering and collaborative analytics.
• Apache Spark for scalable data processing.
• SQL and NoSQL databases for data storage and retrieval.
• ETL tools for data transformation.

Ideal Candidates

Ideal candidates for the AWS Databricks Cloud Data Engineer position should possess a strong analytical mindset and a passion for data engineering. They should be self-motivated, detail-oriented, and able to thrive in a fast-paced environment while managing multiple priorities. A willingness to collaborate effectively with interdisciplinary teams and a commitment to delivering quality solutions will also be key qualities that contribute to success in this role.