Lead I - Kafka Support Engineer

Role: L3 Support Data Engineer (AWS, Kafka) Key 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 & Qualifications • 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.