Description
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.
Key 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).
- Experience structuring semantic models and feature stores to support data science, predictive modeling, and generative AI/LLM applications.
- Experience implementing end-to-end data observability, lineage tracking, and monitoring frameworks (e.g., OpenTelemetry, Datadog, Prometheus).
- Familiarity leveraging AI-assisted development tools (Copilot, Cursor) and AIOps practices to accelerate development velocity and reliability.
- Demonstrated track record of technical mentorship, driving architectural consensus across matrixed teams, and translating business goals into robust engineering roadmaps.
Benefits
- Medical, dental and vision insurance
- 401(k) plan with a Cisco matching contribution
- Paid parental leave
- Short and long-term disability coverage
- Basic life insurance
- Paid time away (vacation, holidays, sick time)