Jr. Data Engineer - Databricks

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Written by AI from the job title and company, not by 11:59, so some details may not match this job. The employer's own page has the real description.

Overview

The Jr. Data Engineer - Databricks at 11:59 will play a vital role in the development, management, and optimization of data pipelines and infrastructure. This position is designed for individuals who are passionate about working with data and eager to contribute to robust data solutions. The successful candidate will collaborate with cross-functional teams to ensure seamless integration and efficient processing of data while leveraging Databricks to enhance data workflows and analytics capabilities.

Job Responsibilities

• Assist in the design and implementation of scalable data pipelines using Databricks.
• Collaborate with data scientists and analysts to understand data requirements and architecture.
• Monitor and maintain data pipeline performance and reliability.
• Perform data cleansing and transformation activities to ensure data quality.
• Execute data ingestion from various sources into cloud storage solutions.
• Participate in the documentation of data processes and workflows.
• Support troubleshooting and debugging of data-related issues.
• Stay updated with emerging trends and best practices in data engineering.

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, or a related field.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Basic understanding of SQL and NoSQL databases.
• Experience with data processing frameworks such as Apache Spark or similar.
• Solid programming skills in languages such as Python or Scala.
• Understanding of ETL processes and data warehousing concepts.
• Strong analytical and problem-solving abilities.
• Excellent communication skills and the ability to work in a team environment.

Technologies & Tools

The Jr. Data Engineer will utilize a variety of technologies and tools in this role, including Databricks for cloud-based data engineering tasks, Apache Spark for data processing, SQL for database operations, and languages such as Python or Scala for scripting. Additionally, familiarity with tools for monitoring and managing cloud infrastructure will also be essential.

Ideal Candidates

Ideal candidates for this position will possess a proactive approach to problem-solving and a genuine enthusiasm for data engineering. They should demonstrate a strong willingness to learn and adapt to new technologies while effectively collaborating with team members. A keen attention to detail, along with the ability to manage multiple tasks efficiently, will further enhance their success in this role. Candidates who show initiative and creativity in addressing data challenges will thrive in this dynamic environment.