We are looking for an experienced
Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions. The ideal candidate will have strong hands-on experience with cloud-based data platforms, big data processing, and analytics engineering best practices.
Requirements
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using AWS EMR, PySpark, and Python
- Work closely with analytics and business teams to build reliable and high-performance data models
- Optimize data processing workflows for performance, reliability, and cost
- Ensure data quality, integrity, and consistency across data platforms
- Implement CI/CD practices for data pipelines using modern DevOps tools
- Collaborate using version control and follow best engineering practices
Must-Have Skills
- Strong experience with AWS (especially EMR)
- Hands-on experience in Python and PySpark
- Strong SQL and analytical skills
- Experience with data pipeline orchestration and tooling
- Working knowledge of GitHub for version control
- Experience with Jenkins or similar CI/CD tools
- Familiarity with dbt
Good-to-Have Skills
- Experience with Terraform or other Infrastructure-as-Code tools
- Deeper hands-on expertise with dbt
- Exposure to cloud cost optimization and data governance
Nice to Have
- Experience working in Agile environments
- Strong communication and stakeholder collaboration skills
Benefits
What We Offer
- Opportunity to work on large-scale, modern data platforms
- Collaborative and engineering-driven culture
- Competitive compensation and benefits
