Data Engineering Technical Leader - CX AI

About the role

Meet the Team Cisco's Customer Experience (CX) organization is a high-growth, innovation-driven team focused on delivering a unified digital experience for customers and partners. The CX Platform enables diverse CX use cases through modern cloud-native architecture and emerging AI capabilities, including predictive and generative AI. Our team builds scalable, reliable platforms that accelerate customer outcomes, with a strong focus on quality, urgency, ownership, and data-driven decision making.

Your Impact You will be the architectural and technical authority driving our next-generation cloud-native data platform. Operating as a hands-on builder and leader, you will own distributed data pipelines, lakehouse architectures, and backend services end-to-end—powering real-time CX analytics and AI-ready data foundations. You will establish organizational standards for data modeling, streaming, and observability while mentoring engineering pods and aligning technical execution with strategic business priorities.

Responsibilities

• Data Platform Architecture: Architect, build, and optimize scalable cloud-native backend services and data platforms supporting high-throughput ingestion, real-time analytics, and downstream AI/ML consumption.
• Pipeline & Lakehouse Engineering: Design robust batch and streaming ETL/ELT pipelines, implementing event-driven data flows, Change Data Capture (CDC), and modern lakehouse architectures (e.g., Snowflake, Databricks).
• Data Quality & Observability: Establish enterprise-grade standards for data modeling, semantic layers, schema governance, distributed tracing, and real-time telemetry/alerting to ensure high data integrity and reliability.
• API & Service Integration: Define high-performance API contracts (REST, GraphQL) and backend microservices that expose trusted datasets and metrics for self-service reporting and AI applications.
• Technical Leadership & Governance: Drive CI/CD automation, conduct code and design reviews, mentor senior and mid-level data engineers, and coordinate cross-team technical dependencies across platform, security, and product stakeholders.

Minimum Qualifications

• Bachelor’s degree with 8+ years of related experience, or a Masters degree with 6+ years of related experience.
• Experience in Python and SQL for data engineering, automation, and transformation, along with backend development experience in languages such as Go, Java, Node.js, or Rust.
• Experience designing REST or GraphQL APIs, with experience in relational PostgreSQL, MySQL and/or NoSQL databases.
• Experience implementing distributed messaging and streaming systems using Apache Kafka, AWS SQS/SNS, or comparable technologies.
• Experience building and optimizing data platforms using modern lakehouse/warehouse technologies such as Snowflake, Databricks, BigQuery, or AWS Redshift or similar.
• Experience building, maintaining, and troubleshooting automated CI/CD pipelines using Jenkins, GitHub Actions or similar and containerized deployments.

Preferred Qualifications

• Expertise in large-scale data ingestion architectures, Change Data Capture (CDC), and multi-source ETL/ELT across APIs, databases, event streams, and object storage (S3/GCS