Senior Software Engineer - Data Team (AWS, Flink, OpenSearch)

We are seeking a Senior Streaming Platform Engineer (6+ years) with deep expertise in enterprise-scale streaming and cloud data platforms. Based in Atlanta, this role collaborates closely with teams in Salt Lake City and Pune, with reasonable overlapping hours. The ideal candidate brings hands-on experience managing scalable, secure, and highly available streaming ecosystems that support real-time analytics, event-driven architectures, and enterprise data platforms — including exposure to AI-assisted engineering and automation practices.

What You’ll Do

• Administer, optimize, and govern Kafka, AWS MSK, Kinesis, Kafka Connect, and OpenSearch platforms
• Design scalable, fault-tolerant, and secure streaming architectures
• Monitor, troubleshoot, and performance-tune distributed systems; drive capacity planning
• Implement security controls, automation, and operational best practices
• Support integrations with data lakes, Snowflake, analytics platforms, and downstream systems
• Automate infrastructure provisioning using Terraform or similar IaC tools
• Leverage AI-assisted development tools (Claude or equivalent) to improve engineering productivity and platform automation
• Collaborate with engineering and analytics teams to enable real-time data processing and AI-driven data solutions

What We’re Looking For

Required:

• 6+ years of experience with Kafka administration and distributed streaming systems
• Strong AWS cloud services experience (MSK, Kinesis, and related services)

in OpenSearch

• Linux administration and automation/scripting skills
• Python development and platform reliability engineering
• Desire to learn and implement evolving and new technologies
•  

Preferred:

• Experience with Flink using Spring Boot
• Snowflake integration experience
• Kubernetes orchestration
• Administration knowledge in OpenSearch clusters
• Familiarity with AI-enabled engineering workflows and tools

What Success Looks Like

• Streaming platforms operate with high availability, performance, and reliability at enterprise scale
• Governance, security, and automation practices are consistently applied across the ecosystem
• Engineering teams are unblocked and empowered through well-integrated data pipelines and real-time infrastructure
• AI tooling meaningfully improves operational efficiency and engineering velocity