Senior Data Engineer (Snowflake, Lang Graph and Lang Chain)- AI, Hybrid

Cisco•Research Triangle Park, NC

1d•$139,300 - $203,600•Hybrid

About The Position

The Senior Data Engineer will design, build, deploy, and operate technology architectures, solutions, and software for capturing, managing, storing, and using structured and unstructured data from internal and external sources. The role establishes processes and structures that channel data from multiple inputs and store it across cloud-based distributed structures, local databases, and other applicable storage systems. It also develops tools and programming that use AI, machine learning, and big-data techniques to cleanse, organize, and transform data, and to maintain data structures and integrity through automation. The engineer establishes design standards and assurance processes for software, systems, and applications to ensure data connections, flows, and storage are compatible and operable, and reviews business and product requirements to recommend system and storage changes. The role is part of Cisco’s Growth Metrics Data and Analytics team, which works across CX, Finance, and GTM. The team aims to incorporate AI into decision-making and data workflows. The position is based in North Carolina and follows a hybrid work model.

Requirements

Bachelor's degree in Computer Science, Data Engineering, AI/ML, Data Science, or equivalent, with 8+ years of related development experience; or a master's degree with 5+ years of related development experience.
4+ years of hands-on data engineering experience with Snowflake, Snowflake Intelligence/Co-work, dbt, query optimization and performance, data modeling and schema design, incremental processing and pipelines, data quality and validation, warehouse architecture and scaling, cost optimization, and ETL/ELT tooling and orchestration.
Proficiency in data engineering programming languages such as SQL (Snowflake), Teradata, advanced Python, Java, or Scala.
Demonstrated expertise designing and maintaining complex data architectures and pipelines.
Experience with data engineering involving cloud-based storage and distributed structures.
Experience managing data validation, scrubbing, and correlation methodologies for large-scale datasets.

Nice To Haves

Experience applying AI and machine learning techniques to data engineering problems.
Hands-on experience developing and deploying AI/ML solutions in enterprise production environments.
Experience with large language models, transformer architectures, and advanced AI frameworks.
An advanced degree in AI/ML, Computer Science, or a related technical field.
Knowledge of vector databases, retrieval-augmented generation (RAG), and semantic search systems.
Expertise in generative AI, prompt engineering, and model fine-tuning.
Experience with responsible AI practices, model governance, and enterprise AI ethics frameworks.
Experience with multi-agent AI and MLOps tools such as Kubeflow.
Strong analytical skills, including identifying patterns and determining appropriate problem-solving approaches.
Excellent communication skills and ability to collaborate across global teams and business units.
Experience with threat modeling and ensuring data security and privacy compliance within data pipelines.

Responsibilities

Design and implement scalable data architectures for storing, processing, and analyzing high-volume datasets.
Manage the development of robust data pipelines, improve feature engineering, and use knowledge of databases, cloud services, and scripting languages to build models.
Maintain data quality using validation, scrubbing, and imputation techniques.
Write clean, functional code with unit tests and conduct code reviews to identify risks.
Contribute to feature threat modeling and ensure data compliance and security standards are followed.
Partner with data scientists and business stakeholders to articulate and resolve complex problems.
Design reporting and visualization tools that communicate actionable insights and connect data outcomes to business goals.
Lead moderately complex, end-to-end projects and drive technical analysis from initial design through completion.
Recommend data sources, methodologies, and analytics tools to address business needs.
Design and implement complex AI agent orchestration systems using Lang Graph and Lang Chain for enterprise-scale automation.
Establish processes for routing data from multiple inputs and storing it in suitable cloud, database, or other storage systems.
Develop automated tools and programming to cleanse, organize, and transform data and maintain data structures and integrity.
Create design standards and assurance processes to ensure compatibility and operability of data connections, flows, and storage.
Review business and product requirements for data operations and recommend system and storage changes.

Benefits

Medical, dental, and vision insurance, subject to plan eligibility rules.
401(k) plan with a Cisco matching contribution.
Paid parental leave.
Short- and long-term disability coverage.
Basic life insurance.
Potential grants of Cisco restricted stock units, subject to continued employment and vesting terms.
10 paid holidays per full calendar year and one floating holiday for non-exempt employees.
One paid day off for an employee's birthday, a paid year-end holiday shutdown, and four paid personal wellness days.
Non-exempt employees receive 16 days of paid vacation per full calendar year, accrued for full-time employees.
Exempt employees participate in a flexible vacation time-off program with no defined usage limit, subject to availability and business limitations.
80 hours of sick time provided on hire and each January 1, with up to 80 unused hours carried forward.
Additional paid time away may be requested for critical or emergency family issues.
Optional 10 paid volunteer days per full calendar year.
For non-sales roles, eligibility to earn annual bonuses subject to Cisco policies.