Data Engineer
EXL · United States
Business Consulting and Services · 10,001+ employees
7 h ago
Mid (2-5 yrs)
Full-time
United States
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About the role
Design and maintain scalable data pipelines and ETL/ELT frameworks using Python and PySpark. Develop reusable components and automation solutions while adhering to software engineering best practices.
What they look for
Python
PySpark
AWS
Snowflake
SQL
Data Modeling
Microservices
CI/CD
Git
ETL/ELT
Software Engineering
API Gateway
Requirements
Requires 3-6 years of experience with strong expertise in Python, PySpark, AWS cloud services, and Snowflake. A degree in Computer Science or a related engineering field is required.
Full description
Key Responsibilities Application & Data Development
- Design, develop, and maintain scalable data pipelines, applications, and utilities using Python and PySpark.
- Build robust ETL/ELT frameworks and data processing solutions for large-scale datasets.
- Develop reusable components, libraries, and automation solutions following coding standards and best practices.
- Write clean, maintainable, and efficient code with proper error handling and logging.
- Participate in code reviews and ensure adherence to development standards.
Must-Have Skills
- Strong hands-on development experience in Python.
- Experience with PySpark and large-scale data processing.
- Strong understanding of software engineering principles, coding standards, design patterns, and best practices.
- Experience with AWS Cloud services such as Glue, Lambda, S3, EC2, API Gateway, ECS, etc.
- Hands-on experience with Snowflake or other cloud data platforms.
- Solid understanding of relational and non-relational databases.
- Experience developing Microservices.
- Knowledge of CI/CD pipelines, Git, version control, and DevOps practices.
- Strong SQL and data modeling skills.
- Excellent analytical, debugging, and problem-solving skills.
- Strong communication and stakeholder management skills
