Productivity Data Engineer & Strategist
Cisco is hiring a Productivity Data Engineer & Strategist. Level rates it ; you can apply on Level.
Level's read on this job
- Works on AI ●●●○ is how Level rates this data engineer role: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Copilot, Python and SQL.
- Level files it as a senior role.
- Level lists 1,400+ other open roles at Cisco.
- The role was posted in the last few days.
AI in this role
Productivity Data Engineer & Strategist to manage enterprise platforms and design semantic models for AI-assisted business intelligence.
Meet the Team
Join the Workforce Productivity Applications team within Cisco IT, where we support all third-party enterprise applications. Our team manages enterprise platforms while leveraging artificial intelligence and creativity to deliver best-in-class IT productivity solutions. We focus on reducing friction, increasing automation, and mitigating security risk in a dynamic, global Agile environment alongside innovative colleagues. Be part of an exciting role evolution from data scientist and machine learning engineer to AI engineer.
Your Impact
- Data Architecture: Develop and implement data architecture to store, process, analyze, and visualize large, high-volume datasets.
- Governance & Compliance: Establish and enforce data governance frameworks, data quality standards, and privacy compliance—including regional requirements such as GDPR and country-specific legislation such as workers councils.
- Technical Guidance: Guide technical peers on database and data lake sources, as well as security requirements such as RBAC/ABAC, row- and column-level security, masking/tokenization, key management, PII classification
- Insights & BI: Translate complex data structures into actionable insights using Business Intelligence and analytics tools such as Tableau or Power BI including building organization-wide dashboards for tracking measurements, usage and KPI’s for email, SaaS applications, and productivity suites.
- Collaboration: Collaborate with engineers and business stakeholders to understand, articulate, and resolve business problems, alongside related security and privacy concerns.
- AI-Enabled Analytics: Design semantic models and certified datasets that make natural-language and AI-assisted BI reliable - Power BI Copilot, Microsoft Fabric, Tableau Agent/Pulse or Snowflake Cortex - including the measure definitions, field descriptions, and synonyms these tools depend on to return trustworthy answers.
Minimum Qualifications
- Education & Experience: Bachelor’s degree with 7+ years of related experience, Master’s degree with 4+ years of related experience, or Ph.D. with 1+ year of related experience.
- Data Modeling: Proven capability in enterprise data modeling (dimensional, relational, and NoSQL) and the design of robust data warehouses and data lakes.
- Technical Proficiency: Proficiency in core programming and querying languages essential for data orchestration and analytics, primarily Python, SQL, dbt, and Snowflake.
- Core Competencies: Excellent communication and strategic planning skills, combined with a self-motivated approach and a strong focus on execution.
- Data Pipelines: Demonstrated ability to ensure data quality while creating and maintaining optimal data pipelines.
Preferred Qualifications
- Advanced Pipeline Engineering: Advanced expertise in designing, building, and optimizing scalable data pipelines, ETL/ELT workflows, and distributed data processing frameworks.
- Reporting & Visualization: Experience designing and creating reporting and visualization solutions to communicate data insights and directly link data to business outcomes.
- Hands-on experience enabling and tuning natural-language/AI features in a BI platform (e.g., Power BI Copilot, Tableau Agent, Snowflake Cortex Analyst), including the semantic-model preparation required for accurate results.
Why Cisco?
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
How we rate this
Productivity Data Engineer & Strategist at Cisco rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where data architecture was part of your work. What did you do?
- Tell me about a project where data governance was part of your work. What did you do?
- Tell me about a project where data modeling was part of your work. What did you do?
- Tell me about a project where business intelligence was part of your work. What did you do?
- Tell me about a project where ai enabled analytics was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Architecture, Data Governance, Data Modeling, Business Intelligence, and AI Enabled Analytics. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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