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 play a pivotal role in harnessing the power of cloud-based solutions to process and analyze large datasets effectively. This position entails designing, implementing, and maintaining data pipelines that seamlessly integrate with AWS and Databricks platforms. The ideal candidate will collaborate with cross-functional teams to ensure data quality and accessibility while optimizing performance and efficiency in data solutions.

Job Responsibilities

• Design and develop robust data pipelines to ingest, transform, and store data using AWS and Databricks.
• Collaborate with data scientists and analysts to understand data requirements and provide necessary datasets for analysis.
• Monitor and optimize data workflows and pipelines for performance, reliability, and scalability.
• Implement data governance policies to ensure data accuracy, integrity, and compliance with regulatory standards.
• Conduct performance tuning and troubleshooting to identify and resolve issues in data processing.
• Document data engineering processes, best practices, and lessons learned for team reference.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Information Technology, or a related field.
• 3+ years of experience in data engineering, preferably with AWS and Databricks.
• Proficiency in SQL and programming languages such as Python or Scala.
• Experience with big data tools and frameworks, such as Apache Spark, Hadoop, or Kafka.
• Knowledge of data warehousing solutions and ETL processes.
• Strong understanding of data modeling concepts and database technologies.

Technologies & Tools

The AWS Databricks Cloud Data Engineer will utilize various technologies and tools, including Amazon Web Services (AWS) for cloud services, Databricks for big data processing, Apache Spark for data processing tasks, and SQL for data querying and management. Familiarity with version control systems like Git, data visualization tools, and containerization technologies such as Docker may also be beneficial.

Ideal Candidates

Ideal candidates for this position will possess a strong analytical mindset and a passion for data-driven decision-making. They will demonstrate excellent problem-solving skills, adaptability, and attention to detail. A collaborative attitude is essential, along with the ability to communicate effectively with team members and stakeholders. Candidates should be proactive learners who stay updated with industry trends and emerging technologies in data engineering and cloud computing.