# Data Engineer at Cisco

Cisco is hiring a Data Engineer in Bengaluru, India. Level rates it Works on AI ●●●○; you can [apply on Cisco](https://jobsbylevel.com/go/27abc00d-0758-4392-8541-2a398bc3d225?utm_medium=ai-agent).

AI Level 3, AI centrality 65 out of 100. Bangalore, India.

## Details

- Company: [Cisco](https://jobsbylevel.com/companies/cisco)
- AI level: AI Level 3 (score 65 out of 100)
- Location: Bangalore, India
- Posted: October 26, 2026
- Apply: https://jobsbylevel.com/go/27abc00d-0758-4392-8541-2a398bc3d225?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=data-engineer-at-cisco-8b699c

## Prepare for this job

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## Description

Meet the Team Join Cisco's Commerce Intelligence Data & Analytics team, a pivotal group delivering seamless intelligence, advanced analytics, and cutting-edge agentic experiences across our business operations. Our mission is to build a scalable, unified, and AI-ready data foundation that drives high-impact business decisions and automated actions. We achieve this by blending innovation, deep process knowledge, technical expertise, and a relentless focus on business impact, ultimately enhancing operational efficiency and data-driven decision-making at scale. Your Impact As a Data Engineer, you will be instrumental in shaping our data landscape. You'll dive deep into operational processes, explore diverse source systems, and analyze complex data platforms to connect critical commerce operational needs. Your expertise will drive the design, build, and maintenance of a robust data ecosystem, enabling advanced analytical capabilities, AI, and agentic solutions. You'll be responsible for end-to-end ETL/ELT pipeline development for both structured and unstructured data, ensuring data threading and transformation within our Golden layer working with the extended team US time zones. A key aspect of your role will be collaborating with business functions across various time zones to design and own a reusable semantic layer, powering consumption across AI, agentic solutions, dashboards, and various applications. Responsibilities Conduct in-depth exploratory data analysis to uncover trends and patterns in structured and unstructured datasets. Translate complex business requirements into robust data solutions, integrating insights from diverse non-ERP sources with our Enterprise Data Warehouse (EDW). Design, build, and optimize scalable ELT/ETL pipelines to ingest, transform, and publish data into the Snowflake Data Cloud. Develop and maintain high-quality, analytics-ready data models using dbt, emphasizing modular design, reusability, rigorous testing, and maintainability. Design and implement a reusable semantic layer that adheres to architectural standards and supports various consumption patterns (AI, agentic solutions, dashboards). Leverage Snowflake Cortex to integrate AI/LLM capabilities directly into data pipelines, enabling advanced analytics. Design and develop data consumption layers, including dashboards, reports, conversational analytics, and agentic solutions. Champion and enforce data quality, observability, lineage, governance, and access control standards across our AI-ready data architecture. Applies working knowledge of databases, relational databases, cloud services, and scripting languages Contributes to data quality and compliance, including cleansing and scrubbing of data, data integrations and data quality framework Collaborate strategically with data architects, analysts, and business stakeholders to define long-term data strategies and deliver scalable, reliable data solutions. Establish and enforce technical governance, CI/CD best practices, and rigorous version control to ensure the integrity, security, and scalability of our modern data stack. Demonstrated experience applying Agile, Scrum, or Kanban methodologies within a data engineering environment. A self-starter with proven expertise to deliver outcomes with minimal supervision Minimum Qualifications Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience. 5+ years of progressive experience in data engineering, with a proven track record in cloud data warehousing and modern data platform implementations. 2+ years of hands-on experience developing AI and agentic solutions, specifically on platforms like Snowflake, AWS, or GCP. Deep expertise with the Snowflake Data Cloud, encompassing its architecture, security model, and operational best practices. Strong proficiency with dbt (Data Build Tool) for designing, developing, and maintaining data models, including automated

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