Data Engineer

Title: Data Engineer

Location: Charlotte, NC

Duration: 12+ Months

About the Role:

We are looking for a highly skilled Data Engineer to join one of our growing teams supporting a leading financial rating agency. In this role, you will play a critical part in designing and developing scalable data pipelines, transforming complex datasets, and delivering high-quality data solutions to support analytical and business decision-making processes.

If you're passionate about data, have a strong foundation in Python, PySpark, and object-oriented programming, and are eager to work on meaningful financial data systems, this role is for you.

Key Responsibilities:

• Design, develop, and optimize large-scale data pipelines using PySpark and Python.
• Implement and adhere to best practices in object-oriented programming to build reusable, maintainable code.
• Write advanced SQL queries for data extraction, transformation, and loading (ETL).
• Collaborate closely with data scientists, analysts, and stakeholders to gather requirements and translate them into technical solutions.
• Troubleshoot data-related issues and resolve them in a timely and accurate manner.
• Leverage AWS cloud services (e.g., S3, EMR, Lambda, Glue) to build and manage cloud-native data workflows (preferred).
• Participate in code reviews, data quality checks, and performance tuning of data jobs.

Required Skills & Qualifications:

• 3 6 years of relevant experience in a data engineering or backend development role.
• Strong hands-on experience with PySpark and Python, especially in designing and implementing scalable data transformations.
• Solid understanding of Object-Oriented Programming (OOP) principles and design patterns.
• Proficient in SQL, with the ability to write complex queries and optimize performance.
• Strong problem-solving skills and the ability to troubleshoot complex data issues independently.
• Excellent communication and collaboration skills.

Preferred Qualifications (Nice to Have):

• Experience working with AWS cloud ecosystem (S3, Glue, EMR, Redshift, Lambda, etc.).
• Exposure to data warehousing concepts, distributed computing, and performance tuning.
• Familiarity with version control systems (e.g., Git), CI/CD pipelines, and Agile methodologies.
• ErWin experience is highly desired.