Data Engineer

Job Description
We are looking for a Data Engineer to design, build, and optimize scalable data platforms on AWS. The ideal candidate has strong experience with Snowflake, Kafka, MuleSoft, and AWS-native analytics services, and can support both real-time and batch data processing while enabling reporting and advanced analytics.

The opportunity:

• Design, develop, and maintain scalable data pipelines using AWS services
• Build and manage cloud-based data lakes on Amazon S3
• Implement and optimize Snowflake data models for reporting and analytics
• Develop real-time streaming solutions using Apache Kafka
• Integrate enterprise systems using MuleSoft APIs and connectors
• Deploy and manage containerized data workloads on AWS EKS
• Write and optimize complex queries using Amazon Athena

This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.

Required Skills:

• 12+ years of experience
• AWS Cloud Services (S3, Athena, EKS, IAM, monitoring)
• Snowflake (data modeling, performance tuning, reporting)
• Apache Kafka (streaming, producers/consumers, real-time pipelines)
• MuleSoft (API-based integrations, enterprise data flows)
• Amazon EKS (container orchestration, deployment)
• Querying Tools: Amazon Athena
• Data Lakes: S3-based data lake architecture
• Reporting: Snowflake reporting layer
• Analytics & Visualization: Tableau

Nice to Have:

• Python or SQL-based ETL development
• CI/CD for data pipelines
• Infrastructure as Code (Terraform/CloudFormation)
• Experience with large-scale, high-volume data systems