Data Engineer Intern

7 days ago


Cypress, Texas, United States Nationstar Mortgage LLC dba Mr. Cooper. Full time

Are you a college student looking for a challenging and rewarding internship? We're seeking Data Engineer Interns to join our team at Nationstar Mortgage LLC d/b/a Mr. Cooper. This is an excellent opportunity to gain hands-on experience in data engineering, work with a collaborative team, and make a meaningful contribution to the company's success.

About Us

Nationstar Mortgage LLC d/b/a Mr. Cooper is a leading financial services organization dedicated to making the dream of homeownership possible. We offer innovative solutions to real business challenges and empower our employees to make a difference in their communities.

Job Description

We are looking for highly motivated and detail-oriented Data Engineer Interns to assist in extracting data from various sources, including databases, APIs, logs, GCP services, and Kafka streams. As a Data Engineer Intern, you will transform data into a usable format for analysis, considering Snowflake as a data warehousing solution. You will also participate in setting up and managing databases on GCP, utilizing services like BigQuery or Cloud SQL.

  • Key Responsibilities:
  • Assist in extracting data from various sources, including databases, APIs, logs, GCP services, and Kafka streams
  • Transform the data into a usable format for analysis, considering Snowflake as a data warehousing solution
  • Participate in setting up and managing databases on GCP, utilizing services like BigQuery or Cloud SQL
  • Ensure data is stored efficiently and securely within Snowflake and can be easily accessed for analysis
  • Contribute to the development and maintenance of data pipelines using tools like Apache Spark on Databricks to automate the flow of data
  • Implement data quality checks and monitoring for data pipelines and databases to ensure data accuracy and integrity
  • Use Snowflake's features for data validation
  • Collaborate in data modeling, schema design, and optimization of data storage and retrieval within Snowflake on GCP
  • Work with cross-functional teams to integrate data into various systems and applications, ensuring data is available for business intelligence and reporting on GCP
  • Write and maintain scripts and code (e.g., Python, Java, or Scala) to support data engineering tasks, especially within the context of Databricks
  • Gain experience in GCP's cloud platforms for data storage, processing, and analysis, and leverage Databricks for advanced analytics and processing
  • Maintain documentation for data engineering processes, data pipelines, and best practices, ensuring a record of changes and configurations
  • Work closely with data analysts, data scientists, and other team members to understand their data requirements and provide support in data provision using the mentioned technologies
  • Stay updated on the latest data engineering tools, technologies, and best practices, especially those related to GCP, Databricks, Snowflake, and Kafka
Required Skills and Qualifications
  • Basic Qualifications:
  • Expertise in programming languages such as Python, Java, Scala, or SQL
  • Be enrolled full-time and pursuing an undergraduate or graduate degree from an accredited college/university or have graduated within one year of start
  • Proficiency in working with databases (SQL and NoSQL) and ETL (Extract, Transform, Load)
  • Familiarity with cloud platforms like Google Cloud Platform (GCP) and the ability to understand and use cloud-based data storage, processing, and analysis services
  • Demonstrable experience with GCP or similar cloud platforms can be a significant qualification
  • Candidates must have authorization to work permanently in the US without the need for sponsorship
  • Local to DFW
Benefits

We offer a competitive salary of $80,000 per year, paid training, and opportunities for growth and professional development. Our team is passionate about mentorship and providing a supportive environment for our interns to succeed.

Please note that this is an estimate based on the job description and location.



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