Data Engineer - Cyborgwave

Overview

The Data Engineer plays a critical role in managing, optimizing, and overseeing data flow within the organization. This position is essential for ensuring that data is processed and made accessible in a reliable, efficient manner, enabling data scientists and analysts to extract meaningful insights that can drive strategic decisions. By building and maintaining robust data infrastructures, the Data Engineer facilitates the successful implementation of data-driven solutions that align with the business goals. Responsibilities include designing data systems, developing data processing algorithms, and collaborating closely with other team members to define data requirements and improve data quality. As the organization continues to grow and evolve, the Data Engineer will be pivotal in supporting scalable data solutions, enhancing data integration, and promoting best practices across the data landscape.

Key Responsibilities

Design, construct, and maintain scalable data pipelines.

Develop and implement ETL processes to transfer data between systems.

Collaborate with data architects to ensure data integrity and quality.

Optimize data models for performance and reliability.

Work with data scientists and analysts to define data needs and requirements.

Monitor data workflows to ensure optimal performance and prevent data loss.

Implement data governance and compliance frameworks.

Utilize batch and real-time data processing tools.

Perform troubleshooting and debugging of data-related issues.

Maintain up-to-date documentation for data processes and methodologies.

Deploy and manage data in cloud environments.

Evaluate and integrate new data management technologies.

Execute data validation and testing to ensure accuracy.

Participate in code reviews and provide constructive feedback.

Work on automating data collection processes for improved efficiency.

Required Qualifications

Bachelor’s degree in Computer Science, Information Technology, or related field.

4+ years of experience in data engineering or a similar role.

Strong expertise in SQL and relational databases.

Proficiency in programming languages such as Python, Java, or Scala.

Experience with data warehousing solutions like AWS Redshift or Google BigQuery.

Familiarity with big data technologies such as Hadoop and Spark.

Understanding of cloud platforms like AWS, Azure, or Google Cloud.

Experience with data pipeline and workflow management tools.

Knowledge of data governance and security best practices.

Ability to work collaboratively in a team-oriented environment.

Strong analytical and troubleshooting skills.

Excellent communication skills, both verbal and written.

Experience with version control systems like Git.

Ability to work under tight deadlines and manage multiple priorities.

Familiarity with data visualization tools is a plus.

Understanding of machine learning concepts is beneficial.