AWS Databricks Cloud Data Engineer - Remote - 1960

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Job Overview

The AWS Databricks Cloud Data Engineer will play a pivotal role in managing and optimizing data pipelines within the cloud infrastructure, specifically leveraging Databricks on AWS. This individual will be responsible for designing, implementing, and maintaining scalable data solutions, ensuring data quality and integrity, and collaborating with cross-functional teams to meet business objectives. The ideal candidate will bring a combination of technical acumen, problem-solving ability, and a proactive approach to enhance data ingestion, transformation, and storage processes.

Job Responsibilities

• Design, develop, and maintain data pipelines using AWS services and Databricks.
• Implement ETL processes to ensure efficient data extraction, transformation, and loading.
• Collaborate with data architects and data scientists to understand data requirements and provide technical solutions.
• Monitor and optimize performance of data processing workflows.
• Ensure data governance and compliance with industry standards.
• Contribute to the development of data models and architecture designs.
• Provide support for data-related issues, troubleshooting and resolving problems as they arise.
• Document processes and maintain up-to-date technical documentation for all data engineering activities.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Minimum 3 years of experience in data engineering roles, with a focus on AWS and Databricks.
• Strong proficiency in SQL and experience with data modeling and database design.
• Experience with cloud services (AWS) and familiarity with Databricks, Spark, and Python.
• Knowledge of ETL tools and data pipeline frameworks.
• Understanding of data security, governance, and compliance standards.
• Excellent analytical and problem-solving skills; ability to work independently and in a team.

Technologies & Tools

The position requires proficiency in various technologies and tools, notably Amazon Web Services (AWS) for cloud infrastructure, Databricks for data processing and analytics, and Apache Spark for big data handling. Familiarity with SQL databases, data modeling tools, and scripting languages like Python or Scala is essential. Additional knowledge of data visualization tools and experience working with ETL frameworks will also be beneficial to the role.

Ideal Candidates

Ideal candidates for this role will possess a passion for data engineering and a continuous improvement mindset. They should have exceptional attention to detail, strong communication skills, and the adaptability to thrive in a fast-paced, remote work environment. A commitment to quality and a proactive approach to problem-solving will help candidates excel in this role, as well as a collaborative spirit to work effectively with diverse teams across the organization.