We're a high-impact, fast-moving data fabric team within the CX Platform at Cisco, serving as the core of our enterprise data platform. Our team blends data engineering with a strong focus on scalability, infrastructure, and data-intensive workflows. You'll be working alongside seasoned engineers with deep expertise in modern data pipelines, cloud-native architectures, AI/ML integration, and large-scale distributed systems offering exceptional opportunities to learn cutting-edge technologies and advance in a rapidly evolving field.
Your Impact
As a Software Engineer in the team, you will contribute to the design, development, and operation of our comprehensive data fabric an enterprise-grade system that enables data-driven decision-making and high-impact product features across Cisco. You'll work closely with a cross-functional team of engineers, product managers, and data experts to build scalable data infrastructure and intelligent data management capabilities that power internal and external services. You will:
Drive the development of sophisticated and robust logic and backend infrastructure that supports large-scale data and compute workflows.
Collaborate across teams to design solutions that meet performance, reliability, and security requirements.
Contribute to the automation and optimization of engineering processes, improving deployment velocity and system health.
Participate in the full software development lifecycle, from ideation and design to deployment and monitoring.
Help shape engineering standards, technical architecture, and operational best practices within the team.
Requirements: Minimum Qualifications
Bachelor's degree in Computer Science, Computer Engineering, or Electrical Engineering, or a related field from a leading university, or equivalent experience accepted in lieu of degree.
2+ years of professional software engineering experience.
Full proficiency in Python (Go advantage).
Experience with deploying and managing containerized applications using orchestration platforms (Kubernetes, Docker).
Experience with cloud infrastructure platforms (AWS - advantage) and with Linux environments.
Preferred Qualifications
Experience with event-driven architecture and event processing services, including streaming platforms and message brokers (Kafka, Kinesis, RabbitMQ, Redis).
Experience in modern ETL/ELT frameworks (Airflow, Spark, dbt, Snowflake, AWS Glue) for building scalable data pipelines. Hands-on experience with monitoring tools (Prometheus, Grafana, Datadog), observability platforms (Elasticsearch, Logstash, Kibana, Splunk), and data management systems (OpenMetadata, Datahub, Great Expectations).
Hands-on experience in version control (Git) and CI/CD pipelines (Github Actions, Jenkins) for deploying and maintaining data infrastructure.
Strong advantage - Familiarity with Large Language Models (LLMs) and AI/ML integration in data systems, including familiarity with vector databases model embeddings.
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