Data Engineer

Role details

Meet the Team Join Cisco's Commerce Intelligence Data & Analytics team, a strategic group at the forefront of delivering seamless intelligence, advanced analytics, and cutting-edge agentic experiences across our global business operations. Our mission is to architect and build a scalable, unified, and AI-ready data foundation that not only drives high-impact business decisions but also enables automated actions at an enterprise level. 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 play a critical role, driving end to end solutions in alignment with AI ready Data Architecture vision. You will lead projects with deep understanding of complex operational processes, explore diverse source systems, and analyze intricate data platforms to design and implement robust, scalable data and agentic solutions that address critical commerce operational needs. Your expertise will be pivotal in designing, building solutions for long-term maintainability of our robust data ecosystem, enabling advanced analytical capabilities, AI, and agentic solutions by collaborating with extended team across various time zones. You will be responsible for end-to-end ETL/ELT pipeline development for both structured and unstructured data, ensuring optimal data threading and transformation within our Golden layer. A key aspect of your role will be collaborating extensively with team at onsite, business functions and other engineering teams to architect and own a reusable semantic layer, strategically powering consumption across AI, agentic solutions, dashboards, and various enterprise applications. You will also mentor junior engineers and champion best practices across the team. Responsibilities Lead complex exploratory data analysis initiatives to identify strategic trends and patterns within structured and unstructured datasets, informing architectural decisions. Drive the translation of highly complex business requirements into strategic, scalable, and resilient data solutions, integrating insights from diverse non-ERP sources with our Enterprise Data Warehouse (EDW). Architect, design, and oversee the development and optimization of highly scalable ELT/ETL pipelines to ingest, transform, and publish data into the Snowflake Data Cloud, ensuring performance and reliability. Define standards for, and oversee the development and maintenance of, high-quality, analytics-ready data models using dbt, emphasizing modular design, reusability, rigorous testing, and CI/CD integration. Lead the design and implementation of a reusable semantic layer that adheres to enterprise architectural standards and supports diverse, high-volume consumption patterns (AI, agentic solutions, dashboards). Drive the integration of Snowflake Cortex and other AI/LLM capabilities directly into data pipelines, enabling advanced analytics and intelligent automation. Lead the design and development of advanced data consumption layers, including sophisticated dashboards, reports, conversational analytics, and agentic solutions. 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 Establish and champion best practices for data quality, observability, lineage, governance, and access control across our AI-ready data architecture, ensuring data trust and compliance. Serve as a technical liaison, collaborating strategically with data architects, analysts, and business stakeholders to define and execute long-term data strategies and roadmaps. Work in partnership and guidance from the core team at onsite Drive the establishment and continuous improvement of technical governance, CI/CD best practices, and rigorous version control standards to ensure the integrity, security, and scalability of our modern data stack. Experience with cloud-native services for data processing and orchestration (e.g., AWS Glue, Lambda, Step Functions, GCP Dataflow, Cloud Composer). 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 Provide technical guidance and mentorship to junior data engineers, fostering a culture of excellence and continuous learning. Minimum Qualifications Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience. 8+ years of progressive experience in data engineering, with a proven track record in architecting and leading cloud data warehousing and modern data platform implementations. 4+ years of experience leading or architecting AI and agentic solutions, specifically on platforms like Snowflake, AWS, or GCP. Expert-level proficiency and architectural leadership with the Snowflake Data Cloud, encompassing its advanced features, security model, and operational best practices. Expert-level proficiency and strategic application of dbt (Data Build Tool) for designing, developing, and maintaining complex data models, including automated testing and CI/CD integration. Mastery in SQL and Python, with a focus on scalable data processing, automation, and API integration. Extensive experience (7+ years) with leading BI/reporting tools such as Sigma or Power BI, with a deep understanding of data visualization best practices. undefined Preferred Qualifications Demonstrated expertise in implementing and managing data quality, observability, and lineage frameworks and tools across enterprise data pipelines.Deep architectural understanding and practical application of advanced Snowflake capabilities (e.g., zero-copy cloning, secure data sharing, external tables, Snowpark, dyn