Data Engineer

The application window is expected to close on: Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received . 2016712 - Data Engineer (Hybrid) The application window is expected to close on: August 27, 2026 Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received. The role is listed as hybrid – workers in this role are expected to work from the listed office on a semi-regular basis. Meet the Team   The Enterprise Data Foundation & Engineering team is responsible for building and managing the core data platforms, pipelines, and foundational data assets that enable enterprise reporting, analytics, data science, and operational decision-making across the organization.

As a Data Engineer, you will play a key role in designing and delivering scalable, high-quality data solutions that transform complex business data into trusted, accessible, and actionable information. In this role, you will: Design, develop, and optimize enterprise-scale data pipelines and data integration solutions. Build and maintain cloud-native data products, data warehouses, and curated datasets. Lead the implementation of data engineering standards, reusable frameworks, and automation capabilities. Develop scalable ELT/ETL solutions that support both batch and near real-time data processing. Partner with business and technology teams to translate data requirements into technical solutions. Implement data quality, monitoring, observability, and governance controls to ensure trusted data assets. Support enterprise initiatives involving data platform modernization, cloud migration, and advanced analytics. This role offers the opportunity to influence the future of the enterprise data landscape by building foundational capabilities that support strategic business decisions across the organization. You will work with modern cloud technologies, large-scale data platforms, and diverse business domains while helping shape engineering standards and guidelines. The position provides significant exposure to enterprise architecture, cloud transformation initiatives, and emerging data technologies, making it an ideal opportunity for an experienced engineer seeking both technical depth and broad organizational impact. Minimum Qualifications: :   7+ years of relevant experience in data architecture, data engineering, or related fields Data Engineering Expertise: Demonstrated professional experience designing, developing, implementing, and supporting production-grade data integration and ETL/ELT solutions. SQL and Data Warehousing: Proven hands-on experience developing and optimizing complex SQL queries, stored procedures, and data transformations within enterprise-scale relational or cloud data warehouse environments. Platform Proficiency: Documented experience designing and implementing data solutions across both on-premises (e.g., Oracle, Teradata) and cloud-based (e.g., Snowflake, Google BigQuery) data platforms. Pipeline Orchestration: Practical experience developing, deploying, and maintaining automated data pipelines using enterprise orchestration or integration technologies (e.g., Control-M, Informatica, dbt).

Bachelor’s degree in computer science, Information Systems, Engineering, Mathematics, or a related technical field. Demonstrated ability designing and implementing dimensional data models, including star and snowflake schemas, for enterprise reporting and analytics. Experience using Python, or Java for data engineering and data processing solutions. Experience implementing CI/CD processes and source control practices using Git and enterprise DevOps platforms. Experience supporting enterprise data governance, metadata management, data lineage, and data quality frameworks. Experience working with ERP, Sales, Finance, Customer, or Supply Chain data domains.  Why Cisco?  At Cisco, we’re