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.

Job Overview

The AWS Databricks Cloud Data Engineer at Cyrten will be responsible for designing, implementing, and maintaining scalable and efficient data pipelines within the cloud environment. This role involves collaborating with data scientists and analysts, ensuring optimal data processing capabilities, and utilizing Databricks in conjunction with AWS services to facilitate data ingestion, transformation, and storage. The successful candidate will work towards enhancing data reliability and accessibility, ultimately driving informed decision-making across the organization.

Job Responsibilities

• Design, develop, and maintain data processing pipelines using AWS and Databricks.
• Implement ETL processes to ensure seamless data integration from various sources.
• Collaborate with data scientists and stakeholders to optimize data architecture.
• Monitor and troubleshoot data pipeline performance and reliability issues.
• Document data workflows, architecture, and processes for team knowledge sharing.
• Ensure data quality and integrity through rigorous testing and validation.
• Stay updated with new technologies and best practices in data engineering and cloud services.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Proven experience as a Data Engineer or similar role with a strong emphasis on cloud technologies.
• In-depth knowledge of AWS services such as S3, Redshift, Glue, and Lambda.
• Experience with Databricks for big data processing and analytics.
• Proficiency in SQL and experience with programming languages such as Python or Scala.
• Understanding of data modeling, warehousing, and governance principles.
• Familiarity with version control systems such as Git.

Technologies & Tools

The ideal candidate will work primarily with AWS cloud services such as Amazon S3, Redshift, and Glue, along with Databricks for data processing. Other technologies include Apache Spark, SQL, Python, and tools for data visualization and reporting. Familiarity with CI/CD tools and version control systems like Git will also be essential for effective collaboration and deployment of projects.

Ideal Candidates

Ideal candidates for the AWS Databricks Cloud Data Engineer position will possess strong analytical and problem-solving skills, with a keen attention to detail. They should be passionate about data and have a proactive approach to learning new technologies. Excellent communication skills are essential for collaborating with cross-functional teams, and a strong understanding of best practices in data engineering is critical. A customer-focused mindset, resourcefulness, and a commitment to driving data-driven decision-making will also characterize successful applicants.