About the Role
The role involves developing and optimizing data pipelines using Python and related technologies, supporting data integrity and accessibility across analytical platforms.
Responsibilities
- Design and implement robust data processing workflows
- Develop and maintain ETL pipelines for large-scale datasets
- Collaborate with analytics and product teams to define data requirements
- Ensure data quality and consistency across systems
- Optimize database queries and improve system performance
- Integrate data from multiple heterogeneous sources
- Support data modeling and schema design
- Automate data validation and monitoring processes
- Troubleshoot and resolve data pipeline issues
- Document data architecture and engineering practices
- Work with cloud-based data storage and processing solutions
- Implement version control for data pipeline code
- Contribute to data security and access controls
- Participate in code reviews and technical design discussions
- Maintain up-to-date knowledge of data engineering trends
Nice to Have
- Experience with big data technologies such as Spark
- Background in financial or rating data domains
- Knowledge of data governance principles
- Familiarity with monitoring and logging tools
- Experience with infrastructure as code tools
Compensation
Competitive salary based on experience and location
Work Arrangement
Remote
Team
Collaborative team focused on data infrastructure and analytics
About the Team
This role is part of a growing data engineering unit responsible for building and maintaining core data systems that support analytical decision-making across the organization.
What We Offer
- Flexible working hours
- Remote-first culture
- Professional development opportunities
- Health and wellness benefits
- Pension or retirement savings plan
Not available
