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# Data Engineer Remote

- **Company:** Cisco Systems, Inc.
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $103,200 - $146,800
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Configuration Management Databases, Information Systems, Continuous Integration, Information Engineering, Extract Transform Load (ETL), JSON, Python (Programming Language), Security Information and Event Management, SQL Databases, Software Vulnerability Management, YAML, Google Cloud, Data Ingestion, Mttr, Semi-structured Data, Git Flow, Infrastructure Automation Frameworks, Information Technology, Data Analytics, Restful APIs, Data Pipelines, Vulnerability Analysis
- **Published:** October 26, 2026
- **Apply:** https://www.manhattanjobs.com/job.asp?id=3472118436&tx=HT8276THI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field plus 3+ years of relevant experience, or a Master's degree in a related field.
 * Proficiency in Python and SQL with a proven ability to write clean, maintainable code.
 * Demonstrated experience building and operating ETL/ELT pipelines using REST APIs and semi-structured data (JSON, YAML).
 * Experience with Git-based workflows, CI/CD, and data modeling standard processes.
 * Proficiency in AI/ML usage, including the ability to apply AI to data analysis and correlation tasks., * Exposure to security data domains such as vulnerability management, asset inventory, CMDB, or SIEM.
 * Experience with pipeline orchestration tools (e.g., Airflow, Dagster) and transformation frameworks (e.g., dbt).
 * Familiarity with graph data models, relationship-based asset modeling, or AI/ML-driven data analysis.
 * Cloud platform experience (AWS, Azure, GCP) and Infrastructure-as-Code (IaC) principles.
 * Experience operating within large-scale, federated, or decentralized enterprise environments.

## Description

In this role, you will become the Domain Expert for our data pipelines, moving us from reactive monitoring to proactive, data-driven security. You will own the data ingestion and attribution layer, ensuring that every asset and vulnerability is accurately traced to its owner, business unit, and criticality tier. This role is highly impactful, as it directly bridges the gap between raw, noisy security data and actionable findings, ultimately reducing our Mean Time to Remediation (MTTR). You will also have the opportunity to influence our transition toward AI-augmented data analysis and automated correlation., * Design, build, and maintain robust data pipelines that ingest and normalize security data from a diverse array of sources (e.g., asset inventory, vulnerability scanners, cloud providers, and identity systems).

 * Operate and improve the attribution layer by implementing entity resolution and ownership assignment rules as version-controlled code.
 * Establish data quality monitoring to detect anomalies, missing data, or correlation failures, ensuring high visibility before issues impact end-users.
 * Develop automated correlation logic for complex infrastructure scenarios where conventional identification keys fail.
 * Collaborate with analysts and leadership to provide query support, reporting, and executive metrics that drive security program decisions.