Lead I - Kafka Support Engineer

Job Summary

Role: L3 Support Data Engineer (AWS, Kafka)

Responsibilities

• Advanced Troubleshooting Incident Management: Provide Tier-3 (L3) operational support and deep-dive troubleshooting for real-time data pipelines, distributed systems, and production bottlenecks using Apache Kafka (MSK or Confluent) and AWS services.
• Pipeline Development Maintenance: Develop, maintain, and debug real-time data pipelines to ensure continuous, reliable data delivery.
• Kafka Ecosystem Management: Configure, manage, and troubleshoot Kafka connectors, producers, consumers, brokers, topics, and schema registries to guarantee seamless data flow and integration across enterprise systems.
• ETL/ELT Workflow Optimization: Support, design, and implement scalable ETL/ELT workflows capable of processing large volumes of data efficiently, resolving performance degradation issues.
• AWS Data Stack Optimization: Monitor, troubleshoot, and optimize data lake and data warehouse solutions leveraging AWS services including Lambda, S3, and Glue.
• Observability Reliability: Implement and enhance robust monitoring, automated testing, and observability practices (metrics, logs, traces) to proactively identify platform vulnerabilities and ensure reliability.
• Security Governance: Uphold stringent data security, governance, and compliance standards across all data operations and support workflows.
• Cross-Functional Collaboration: Communicate technical findings clearly to both engineering peers and leadership during critical incident resolutions and post-mortems.

Requirements

• Experience: Minimum of 5 years of experience in data engineering, software engineering, or high-tier technical support/SRE roles within distributed environments.
• Core Technical Expertise: Proven expertise with Apache Kafka and the modern AWS data stack (MSK, Glue, Lambda, S3, CloudWatch, etc.).
• Programming Proficiency: Proficient in coding, debugging, and code review with Python, SQL, and Java (Java strongly preferred). Must demonstrate the flexibility to write and troubleshoot code in both Python and Java.
• DevOps Infrastructure: Experience with infrastructure-as-code (IaC) tools such as CloudFormation and managing CI/CD deployment pipelines.
• Analytical Problem-Solving Skills: Exceptional analytical mindset with a systematic approach to debugging complex, distributed, asynchronous systems under pressure.
• Communication Skills: Excellent verbal and written communication abilities, with a proven track record of translating complex technical roadblocks into actionable solutions for cross-functional teams and stakeholders.

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