Security Architect
SQA Solution
ModernaJoining Moderna offers the unique opportunity to be part of a pioneering team that's revolutionizing medicine through mRNA technology, with a diverse pipeline of development programs across various diseases.
As an employee, you'll be part of a continually growing organization, working alongside exceptional colleagues and strategic partners worldwide, contributing to global health initiatives.
Moderna's commitment to advancing the technological frontier of mRNA medicines ensures a challenging and rewarding career experience, with the potential to make a significant impact on patients' lives worldwide.
We are advancing vulnerability risk management by building an evidence-driven data plane that connects asset, vulnerability, threat, remediation, and business-context signals into prioritized action. This role offers the opportunity to shape how Moderna turns high-volume security data into reliable, model-ready products that support risk modeling, owner action, and executive visibility.
As AI-driven discovery increases vulnerability volume and ownership sprawl, this role will help adapt detection, triage, and data products so teams can identify accountable owners, prioritize the right work, and lay the groundwork for future shift-left scanning and unified remediation workflows across code, artifacts, and platforms.
We are seeking a Senior Security Data Engineer, Vulnerability Risk Management to own and scale the data products across the full lifecycle: raw source ingestion, normalized evidence, risk model outputs, and operational reporting.
This is a high-impact, hands-on role for a self-starter who treats security data as a product, balancing engineering rigor, pragmatic normalization, data quality, and business value.
Design, build, and operate reliable ingestion pipelines for asset, vulnerability, finding, remediation, threat intelligence, and business-context data sources.
Build reusable ingestion patterns that can absorb new sources without brittle, one-off logic.
Support batch and incremental processing patterns from raw source capture through normalized, model-ready data products.
Partner with source-system owners to clarify schema changes, source freshness, field semantics, and operational constraints.
Own transformations from raw evidence into normalized security entities such as assets, vulnerabilities, findings, owners, exposure context, risk-reduction actions, and validation states.
Engineer model-ready features that encode asset ownership, exposure, business importance, exploitability, remediation state, and organizational context.
Support risk model outputs and operational reporting datasets used by remediation owners and leadership.
Model ownership and accountability signals across code, artifacts, platforms, infrastructure, and application contexts to reduce ambiguity in remediation routing.
Make pragmatic normalization decisions for messy, heterogeneous data while documenting assumptions, confidence, and tradeoffs.
Adapt vulnerability detection and triage data flows to support increasing AI-driven finding volume without losing ownership, severity, or remediation context.
Build data foundations for scanning workflows across code repositories, build artifacts, deployed platforms, and runtime environments.
Connect vulnerability signals to remediation workflow needs, including owner routing, action state, validation evidence, exception paths, and closure reporting.
Partner with security, engineering, and platform teams to unify how findings are represented from discovery through remediation.
Implement data quality checks for schema validity, completeness, freshness, duplication, drift, and unexpected distribution changes.
Maintain lineage documentation so risk scores, reports, and owner views can be traced back to source inputs.
Build monitoring, alerting, and runbooks for data pipeline reliability and source degradation.
Partner with downstream users to resolve data defects and improve trust in pipeline outputs.
Prepare reliable, pre-aggregated data products for dashboards, operational views, risk reporting, and experimentation.
Collaborate with partners to translate new questions into durable data features.
Improve data contracts, documentation, and self-service access patterns for technical and non-technical stakeholders.
Continuously refine feature hypotheses and data products as the vulnerability risk model and remediation operating model mature.
5+ years of experience in data engineering, analytics engineering, security data engineering, or related technical disciplines.
Strong hands-on proficiency with Python and SQL in production data pipeline environments.
Experience designing, building, and operating ETL/ELT pipelines across heterogeneous source systems.
Experience with data modeling, schema evolution, incremental processing, and data quality controls.
Ability to work with messy, incomplete, or inconsistent datasets and make pragmatic normalization decisions.
Experience supporting data products from source ingestion through reporting, analytics, model inputs, or decision-support outputs.
Experience designing data models that support ownership routing, triage, workflow state, or operational decision-making.
Strong analytical, troubleshooting, documentation, and communication skills.
Here’s What You’ll Bring to the Table (Preferred Qualifications)
Experience with medallion, lakehouse, or data-product architecture patterns.
Experience engineering features for probabilistic, predictive, prioritization, or risk models.
Experience in regulated environments such as biotech, pharmaceutical, healthcare, GxP, SOX, or similar control environments.
Exposure to cybersecurity, vulnerability management, threat intelligence, security operations, or security data platforms.
Exposure to application security, software supply chain security, shift-left scanning, artifact security, platform security, or unified remediation workflows.
Experience building lineage, observability, monitoring, and operational runbooks for critical data pipelines.
Familiarity with orchestration, data catalog, data contract, business intelligence, or operational reporting patterns.
Exposure to AI/Agentic/LLM-assisted coding tools
At Moderna, we believe that when you feel your best, you can do your best work. That’s why our benefits and well-being resources are designed to support you—at work, at home, and everywhere in between.
Since our founding in 2010, we have aspired to build the leading mRNA technology platform, the infrastructure to reimagine how medicines are created and delivered, and a world-class team. We believe in giving our people a platform to change medicine and an opportunity to change the world.
By living our mission, values, and mindsets every day, our people are the driving force behind our scientific progress and our culture. Together, we are creating a culture of belonging and building an organization that cares deeply for our patients, our employees, the environment, and our communities.
We are proud to have been recognized as a Science Magazine Top Biopharma Employer, a Fast Company Best Workplace for Innovators, and a Great Place to Work in the U.S.
If you want to make a difference and join a team that is changing the future of medicine, we invite you to visit modernatx.com/careers to learn more about our current opportunities.
Moderna is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry or citizenship, ethnicity, disability, military or protected veteran status, genetic information, sexual orientation, marital or familial status, or any other personal characteristic protected under applicable law. Moderna is a place where everyone can grow. If you meet the Basic Qualifications for the role and you would be excited to contribute to our mission every day, please apply!
Moderna is an E-Verify Employer in the United States. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.
We’re focused on attracting, retaining, developing, and advancing our employees. By cultivating a workplace that values diverse experiences, backgrounds, and ideas, we create an environment where every employee can contribute their best.
Moderna is committed to offering reasonable accommodations to qualified job applicants with disabilities. Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should contact the Accommodations team at .
Originally posted on Himalayas
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ModernaJoining Moderna offers the unique opportunity to be part of a pioneering team that's revolutionizing medicine through mRNA technology, with a diverse pipeline of development programs across various diseases.
As an employee, you'll be part of a continually growing organization, working alongside exceptional colleagues and strategic partners worldwide, contributing to global health initiatives.
Moderna's commitment to advancing the technological frontier of mRNA medicines ensures a challenging and rewarding career experience, with the potential to make a significant impact on patients' lives worldwide.
We are advancing vulnerability risk management by building an evidence-driven data plane that connects asset, vulnerability, threat, remediation, and business-context signals into prioritized action. This role offers the opportunity to shape how Moderna turns high-volume security data into reliable, model-ready products that support risk modeling, owner action, and executive visibility.
As AI-driven discovery increases vulnerability volume and ownership sprawl, this role will help adapt detection, triage, and data products so teams can identify accountable owners, prioritize the right work, and lay the groundwork for future shift-left scanning and unified remediation workflows across code, artifacts, and platforms.
We are seeking a Senior Security Data Engineer, Vulnerability Risk Management to own and scale the data products across the full lifecycle: raw source ingestion, normalized evidence, risk model outputs, and operational reporting.
This is a high-impact, hands-on role for a self-starter who treats security data as a product, balancing engineering rigor, pragmatic normalization, data quality, and business value.
Design, build, and operate reliable ingestion pipelines for asset, vulnerability, finding, remediation, threat intelligence, and business-context data sources.
Build reusable ingestion patterns that can absorb new sources without brittle, one-off logic.
Support batch and incremental processing patterns from raw source capture through normalized, model-ready data products.
Partner with source-system owners to clarify schema changes, source freshness, field semantics, and operational constraints.
Own transformations from raw evidence into normalized security entities such as assets, vulnerabilities, findings, owners, exposure context, risk-reduction actions, and validation states.
Engineer model-ready features that encode asset ownership, exposure, business importance, exploitability, remediation state, and organizational context.
Support risk model outputs and operational reporting datasets used by remediation owners and leadership.
Model ownership and accountability signals across code, artifacts, platforms, infrastructure, and application contexts to reduce ambiguity in remediation routing.
Make pragmatic normalization decisions for messy, heterogeneous data while documenting assumptions, confidence, and tradeoffs.
Adapt vulnerability detection and triage data flows to support increasing AI-driven finding volume without losing ownership, severity, or remediation context.
Build data foundations for scanning workflows across code repositories, build artifacts, deployed platforms, and runtime environments.
Connect vulnerability signals to remediation workflow needs, including owner routing, action state, validation evidence, exception paths, and closure reporting.
Partner with security, engineering, and platform teams to unify how findings are represented from discovery through remediation.
Implement data quality checks for schema validity, completeness, freshness, duplication, drift, and unexpected distribution changes.
Maintain lineage documentation so risk scores, reports, and owner views can be traced back to source inputs.
Build monitoring, alerting, and runbooks for data pipeline reliability and source degradation.
Partner with downstream users to resolve data defects and improve trust in pipeline outputs.
Prepare reliable, pre-aggregated data products for dashboards, operational views, risk reporting, and experimentation.
Collaborate with partners to translate new questions into durable data features.
Improve data contracts, documentation, and self-service access patterns for technical and non-technical stakeholders.
Continuously refine feature hypotheses and data products as the vulnerability risk model and remediation operating model mature.
5+ years of experience in data engineering, analytics engineering, security data engineering, or related technical disciplines.
Strong hands-on proficiency with Python and SQL in production data pipeline environments.
Experience designing, building, and operating ETL/ELT pipelines across heterogeneous source systems.
Experience with data modeling, schema evolution, incremental processing, and data quality controls.
Ability to work with messy, incomplete, or inconsistent datasets and make pragmatic normalization decisions.
Experience supporting data products from source ingestion through reporting, analytics, model inputs, or decision-support outputs.
Experience designing data models that support ownership routing, triage, workflow state, or operational decision-making.
Strong analytical, troubleshooting, documentation, and communication skills.
Here’s What You’ll Bring to the Table (Preferred Qualifications)
Experience with medallion, lakehouse, or data-product architecture patterns.
Experience engineering features for probabilistic, predictive, prioritization, or risk models.
Experience in regulated environments such as biotech, pharmaceutical, healthcare, GxP, SOX, or similar control environments.
Exposure to cybersecurity, vulnerability management, threat intelligence, security operations, or security data platforms.
Exposure to application security, software supply chain security, shift-left scanning, artifact security, platform security, or unified remediation workflows.
Experience building lineage, observability, monitoring, and operational runbooks for critical data pipelines.
Familiarity with orchestration, data catalog, data contract, business intelligence, or operational reporting patterns.
Exposure to AI/Agentic/LLM-assisted coding tools
At Moderna, we believe that when you feel your best, you can do your best work. That’s why our benefits and well-being resources are designed to support you—at work, at home, and everywhere in between.
Since our founding in 2010, we have aspired to build the leading mRNA technology platform, the infrastructure to reimagine how medicines are created and delivered, and a world-class team. We believe in giving our people a platform to change medicine and an opportunity to change the world.
By living our mission, values, and mindsets every day, our people are the driving force behind our scientific progress and our culture. Together, we are creating a culture of belonging and building an organization that cares deeply for our patients, our employees, the environment, and our communities.
We are proud to have been recognized as a Science Magazine Top Biopharma Employer, a Fast Company Best Workplace for Innovators, and a Great Place to Work in the U.S.
If you want to make a difference and join a team that is changing the future of medicine, we invite you to visit modernatx.com/careers to learn more about our current opportunities.
Moderna is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry or citizenship, ethnicity, disability, military or protected veteran status, genetic information, sexual orientation, marital or familial status, or any other personal characteristic protected under applicable law. Moderna is a place where everyone can grow. If you meet the Basic Qualifications for the role and you would be excited to contribute to our mission every day, please apply!
Moderna is an E-Verify Employer in the United States. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.
We’re focused on attracting, retaining, developing, and advancing our employees. By cultivating a workplace that values diverse experiences, backgrounds, and ideas, we create an environment where every employee can contribute their best.
Moderna is committed to offering reasonable accommodations to qualified job applicants with disabilities. Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should contact the Accommodations team at .
Originally posted on Himalayas