Data Engineer
Cisco · Posted Oct 15
Networking, cloud, cybersecurity, and enterprise IT infrastructure services
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About the role
Cisco's Centralized Analytics Team builds and operates the data platform and analytics foundations that Cisco's pricing, reporting, and AI initiatives run on, owning the path from enterprise data warehouse through to governed, self-service analytics. The team delivers trustworthy data products, semantic models, and serving layers to partner organizations including the Pricing Team. This role works at the intersection of data engineering, platform engineering, and data governance, building batch and streaming pipelines, semantic and dimensional models, and observable ETL/ELT on Snowflake and Databricks so analytics and AI teams can build on data they can trace and trust.
What you will do
- Design, build, and operate batch and streaming data pipelines on Snowflake and/or Databricks
- Turn reference architectures and data contracts from the Principal AI Data Architect into robust, production-grade implementations
- Deliver reliable, observable, cloud-native ETL/ELT for both structured and unstructured data
- Modernize legacy jobs with measurable gains in latency, reliability, and cost
- Implement the semantic models, dimensional schemas, and entity-centric structures that make data trustworthy and reusable
- Maintain the metadata, catalog, and lineage that let any downstream consumer trace an output back to its source
- Build the low-latency APIs, materialized views, and serving layers that power dashboards, reporting, and ML/AI applications
- Embed data quality checks, RBAC/ABAC, masking, and encryption directly into your pipelines
- Instrument workflows with logs and metrics so failures are caught before consumers see them
- Automate testing, deployment, and rollback through CI/CD — a pipeline isn't "done" until it's tested, observable, and in an automated deployment workflow
Skills used in this role
What the employer is looking for
- Bachelor's degree in Computer Science or a related field
- 5–8 years of hands-on data engineering or software engineering experience building production data platforms
- Cloud Data Platforms – Proven experience building and operating cloud-native pipelines on Databricks (PySpark, Delta Lake) and/or Snowflake, with modern orchestration tooling (Airflow, dbt, Dagster, or equivalent).
- Batch & Streaming Processing – Strong production experience with both batch and streaming data processing (Kafka, Spark Structured Streaming, Kinesis, or equivalent).
- Python, SQL & Data Modeling – Strong Python and SQL, with data modeling depth across dimensional, star/snowflake, and entity-centric patterns, and a track record of performance and cost tuning.
- Data Quality & Observability – Practical experience implementing data quality checks, monitoring, and observability for production pipelines.
- Cloud, CI/CD & Containers – Hands-on with AWS and/or Azure services (S3, Glue, Lambda, ADLS, Data Factory, or equivalents), plus CI/CD (GitHub Actions, Jenkins, Azure DevOps) and containers (Docker/Kubernetes).
- Data Governance – Working knowledge of access control, masking, encryption, lineage, and auditability.
Preferred qualifications
- Infrastructure as Code – Practical exposure to Terraform or equivalent IaC tooling for provisioning and managing data infrastructure.
- Search & Vector Platforms – Experience with OpenSearch, pgvector, or similar search and retrieval platforms.
- Knowledge Graphs – Familiarity with graph data stores such as Neo4j and entity-relationship modeling at scale.
- ML & AI Pipeline Exposure – Exposure to embedding pipelines, vector search, MLflow, or ML/LLMOps tooling, and general familiarity with how data pipelines feed model training and inference. Welcome but not required — we'll teach you that side.
- Cloud Cost Awareness – Interest in right-sizing cloud resources and improving the efficiency of automation and data pipelines.
Benefits and support
- Compensation and benefits are detailed in the job posting
About Cisco
Cisco Systems, Inc. is a worldwide leader in IT, networking, and cybersecurity solutions that transform how people connect, communicate, and collaborate. The company specializes in routing, switching, data center infrastructure, and software-defined networking designed for enterprises of all sizes. Today, Cisco drives major advancements in AI infrastructure, observability, and secure hybrid work platforms.
- Industry
- Networking
- Company size
- 90000+ employees
- Founded
- 1984
- Location
- San Jose, California, USA
- Funding stage
- Public Company
Leadership
Chair and Chief Executive Officer
President and Chief Product Officer
Executive Vice President and Chief Financial Officer
Executive Vice President and Chief People, Policy & Purpose Officer
Executive Vice President and Chief Customer Experience Officer
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