Senior Confluent Kafka Lead / Python Developer

Capgemini•Nashville, TN

19h•Onsite

About The Position

The Confluent Kafka Lead / Python Developer is responsible for designing, building, and operating enterprise-grade event streaming solutions using Confluent Kafka while developing Python-based producers, consumers, and streaming applications. This role blends deep hands on development with technical leadership, ensuring scalable, reliable, and secure real-time data flows across distributed systems.

Requirements

6–10+ years of experience in software or data engineering.
4+ years of hands-on experience with Apache Kafka and/or Confluent Platform.
Strong knowledge of: Kafka internals (brokers, partitions, offsets, consumer groups), Schema Registry and schema evolution, Kafka Connect architectures and connectors.
Strong proficiency in Python for backend and streaming development.
Experience building production-grade services using Python frameworks and libraries.
Experience deploying Kafka and applications in cloud or hybrid environments (AWS, Azure, GCP).
CI/CD pipeline experience (GitHub Actions, Jenkins, GitLab, Azure DevOps).
Infrastructure-as-Code experience (Terraform, CloudFormation, ARM/Bicep).

Nice To Haves

Familiarity with async processing, multithreading, or stream processing patterns is a plus.
Containerization experience (Docker, Kubernetes) preferred.
Experience with ksqlDB, Kafka Streams, or stream processing frameworks (Flink, Spark Streaming).
Exposure to event sourcing or CQRS patterns.
Integration of Kafka with data lakes, warehouses, and analytics platforms.
Confluent or cloud platform certifications.
Experience supporting high-throughput, low-latency systems.

Responsibilities

Lead the design and implementation of enterprise Kafka and Confluent Platform solutions (Kafka, Schema Registry, Connect, ksqlDB).
Define and enforce topic design, partitioning, retention, and schema evolution standards.
Act as technical owner for Kafka clusters across dev, test, and production environments.
Drive best practices for high availability, fault tolerance, and scalability.
Design and develop Python-based Kafka producers and consumers using Confluent Kafka Python APIs.
Build event-driven microservices and streaming applications in Python.
Implement message serialization and schema validation (Avro, JSON, Protobuf).
Handle idempotency, retries, back-pressure, and error handling patterns.
Design event-driven integration patterns bridging microservices, data stores, APIs, and third party systems.
Integrate Kafka with downstream consumers such as databases, data lakes, analytics platforms, and search systems.
Support real-time pipelines for transactions, telemetry, customer events, and analytics.
Collaborate with API, data, and application teams to align event contracts.
Implement Kafka security controls: TLS encryption, SASL / OAuth authentication, ACL-based authorization.
Enforce data governance, schema compatibility rules, and event ownership models.
Ensure compliance with enterprise security and regulatory standards.
Build and maintain CI/CD pipelines for Kafka-related applications and configurations.
Use Infrastructure as Code to provision and manage Kafka infrastructure.
Implement monitoring and alerting using tools such as Confluent Control Center, Prometheus, Grafana, or cloud-native equivalents.
Troubleshoot production streaming issues related to latency, lag, throughput, or data loss.
Serve as Kafka subject matter expert and technical lead.
Mentor developers on event-driven design and streaming best practices.
Review designs and code for Kafka and Python-based streaming solutions.
Partner with architects, SREs, and platform teams on roadmap and capacity planning.