Streaming Data Engineer

Mogi I/O is a company focused on OTT, podcast, and short video applications, and they are seeking a highly experienced Data Engineer to design and optimize scalable cloud-based data platforms on AWS. The role emphasizes real-time and batch data processing to support enterprise analytics and reporting, enabling data-driven decision-making across the organization.

Responsibilities:

• Design, develop, and maintain scalable data pipelines using AWS services
• Build and manage S3-based data lakes for batch and streaming workloads
• Implement and optimize Snowflake data models for analytics and reporting
• Develop real-time data streaming pipelines using Apache Kafka
• Integrate enterprise systems using MuleSoft APIs and connectors
• Deploy and manage containerized data workloads on Amazon EKS
• Write, optimize, and maintain complex SQL queries using Amazon Athena
• Ensure data quality, reliability, and performance across pipelines
• Support reporting and visualization use cases using Snowflake and Tableau
• Collaborate with architects, analytics teams, and business stakeholders

Requirements:

• 12+ years of experience in data engineering or related roles
• Strong hands-on experience with AWS (S3, Athena, EKS, IAM, monitoring)
• Proven expertise in Snowflake data modeling, tuning, and reporting
• Experience building real-time pipelines using Apache Kafka
• Hands-on experience with MuleSoft for API-based enterprise integrations
• Experience deploying and managing workloads on Amazon EKS
• Strong SQL skills and query optimization using Athena
• Experience designing and operating S3-based data lake architectures
• Exposure to analytics and visualization tools such as Tableau
• Experience with Python or SQL-based ETL development
• CI/CD pipelines for data engineering workloads
• Infrastructure as Code using Terraform or CloudFormation
• Experience working with large-scale, high-volume data platforms
• Familiarity with monitoring, logging, and data reliability practices