Data Engineer

Required Skills

• 7+ years of professional experience in Data Engineering or a closely related field
• Strong hands-on Data Engineering experience
• Strong Core Python programming skills with the ability to write code independently
• Strong SQL skills, including complex queries and data manipulation
• Good understanding of Big Data concepts and data processing
• Hands-on experience with Shell/Bash scripting
• Hands-on experience with AWS S3
• Experience designing, developing, testing, and supporting data pipelines / ETL processes
• Strong understanding of data integration, data processing, and data engineering best practices

Good to Have

Experience with one or more of the following technologies is preferred:

• AWS SQS / event-driven architecture
• Microservices
• API Development / REST APIs
• Apache Kafka
• Kubernetes
• Argo / Argo Workflows
• Amazon Redshift
• Amazon Aurora

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and data processing solutions
• Write clean, maintainable and production-ready Python code
• Develop complex SQL queries for data processing and analysis
• Work with large datasets and apply Big Data concepts
• Build and maintain data workflows using AWS services, particularly Amazon S3
• Develop Shell/Bash scripts for automation and data processing
• Integrate data from multiple sources and support reliable data movement and transformation
• Troubleshoot data pipeline and production issues
• Collaborate with application, cloud, architecture, and engineering teams
• Follow best practices for performance, scalability, security, monitoring, and code quality

Ideal Candidate

The ideal candidate is a hands-on Data Engineer, not primarily a BI/reporting or database administration professional.

Candidates should be able to demonstrate:

Core Python + SQL + Big Data + Shell Scripting + AWS S3

as their primary technical skill set, with exposure to event-driven architecture, Kafka, APIs, microservices, Kubernetes, Redshift, or Aurora considered an advantage.

Recruiter Screening – Must Validate

Before submitting a candidate, please confirm:

1. Do they have 7+ years of Data Engineering experience?
2. Can they write Core Python code independently?
3. Do they have strong hands-on SQL experience?
4. Have they worked with Big Data / large-scale data processing?
5. Do they have hands-on Shell/Bash scripting experience?
6. Have they worked hands-on with AWS S3 and AWS-based data pipelines?
7. Do they have experience with any of the preferred technologies such as SQS, Kafka, APIs, Microservices, Kubernetes, Argo, Redshift, or Aurora?
8. Is their recent experience genuinely Data Engineering, rather than primarily DBA, BI, reporting, or data analysis?