Manufacturing Cybersecurity Data Engineer

GM•Warren, MI

1d•Hybrid

About The Position

General Motors is transforming the future of mobility while operating one of the world’s most complex manufacturing environments. The Manufacturing Cybersecurity team helps protect the technology, systems, and data that keep GM plants safe, resilient, and productive. As a Manufacturing Cybersecurity Engineer, you’ll build and operate the data foundation that enables OT cyber-risk visibility across GM manufacturing. You’ll develop reliable data-ingestion and ETL solutions that consolidate vulnerability, asset, configuration, and security telemetry from plant systems, cybersecurity tools, enterprise platforms, and other sources into the Databricks Lakehouse Platform. Using Python, SQL, scripting, and data-quality practices, you’ll transform, validate, monitor, and troubleshoot pipelines, then translate complex technical data into actionable insights through Power BI or similar dashboards and reports. This is a hands-on Level 6 individual contributor role. You’ll exercise independent judgment to resolve non-routine data and cybersecurity problems, propose process improvements, and coordinate delivery across cybersecurity, manufacturing, plant, data engineering, and technology stakeholders. Your work will help plant teams prioritize remediation, reduce OT exposure, and make informed decisions without disrupting production.

Requirements

Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, Data Engineering, Engineering, or a related field, or equivalent relevant experience.
3+ years of professional experience in cybersecurity, data engineering, analytics, software engineering, manufacturing technology, or a related field.
Hands-on experience developing and supporting production data pipelines using Python, SQL, scripting, ETL, or data-ingestion technologies.
Experience integrating and validating data from multiple enterprise, plant, cybersecurity, or operational technology sources, with the ability to diagnose data-quality and pipeline issues.
Experience with OT or industrial control system cybersecurity, vulnerability management, asset inventory, security telemetry, or cyber-risk reporting.
Ability to work independently, exercise sound judgment, and resolve non-routine data and cybersecurity problems in a complex environment.
Ability to communicate technical findings clearly and collaborate effectively with cybersecurity, manufacturing, plant, data engineering, and technology stakeholders.

Nice To Haves

Experience with Databricks, Delta Lake, Spark, cloud data platforms, Lakehouse architecture, or similar technologies.
Experience developing Power BI or similar dashboards, reports, metrics, and visualizations for technical, operational, or executive audiences.
Experience working in a manufacturing, plant, industrial automation, or other operational technology environment.
Familiarity with PLCs, HMIs, SCADA, industrial networks, or comparable systems.
Knowledge of data-governance practices, including data ownership, metadata, lineage, access controls, retention, quality standards, and documentation.
Familiarity with cybersecurity risk-management principles and frameworks such as the NIST Cybersecurity Framework, NIST SP 800-53, or ISO/IEC 27001/27002.

Responsibilities

Design, develop, operate, and maintain dependable data ingestion and ETL pipelines that consolidate OT vulnerability, asset, configuration, and cyber-risk data from multiple sources.
Develop Python, SQL, and scripting solutions for data extraction, transformation, validation, enrichment, automation, and analysis.
Establish data-quality checks, reconciliation routines, monitoring, alerting, and troubleshooting procedures that improve data completeness, accuracy, timeliness, and reliability.
Identify, assess, track, and report OT cybersecurity risks and vulnerabilities across plant systems and networks, supporting risk-based prioritization and remediation planning.
Develop and maintain Power BI or similar dashboards, reports, metrics, and visualizations that communicate exposure, trends, control coverage, remediation progress, and operational performance.
Translate complex technical and security data into clear insights and recommendations for plant teams, cybersecurity stakeholders, manufacturing leadership, and technology partners.
Partner with cybersecurity, manufacturing engineering, plant operations, data engineering, and technology teams to define requirements, resolve data issues, and deliver cross-functional solutions.
Document data sources, data models, pipeline logic, controls, lineage, operating procedures, and troubleshooting guidance in a clear and maintainable format.
Automate repeatable data preparation, analysis, and reporting processes while applying appropriate security, privacy, access-control, and data-governance practices.
Propose and deliver process improvements that increase visibility, reduce manual effort, improve reporting consistency, and strengthen OT vulnerability management.
Communicate status, risks, dependencies, findings, and recommendations clearly; follow issues through resolution and escalate potential impacts early.