Junior Data Security Engineer

Verizon

Alpharetta (GA)

Remote

USD 70,000 - 100,000

Full time

5 days ago
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Benefits offered by this job

Health benefits
401(k) matching
Paid holidays
Paid time off
Tuition assistance

Job summary

Verizon is seeking an entry-level Software Engineer I to join the Data Services team. You will contribute to the MCP server infrastructure powering vulnerability data operations, and you will work on data pipelines and transfers to Google Cloud Storage, enabling analytics sharing across enterprise systems.

You will collaborate with senior engineers, learn end-to-end data platform context, and apply AI tools in daily workflows while expanding cloud capabilities and security practices.

Qualifications

  • Bachelor's degree or 1+ year of relevant work experience.
  • One or more years of software engineering experience.
  • Working Python or .NET (C#) development skills - backend services, REST APIs, data processing.
  • Familiarity with data pipelines and ETL patterns.
  • Understanding of injection vulnerabilities and secure credential handling.
  • Exposure to cloud storage or data transfer patterns (GCS/S3).

Responsibilities

  • Contributing to MCP server tools that expose vulnerability data and security datasets.
  • Implementing feature work and bug fixes across data pipeline services.
  • Building and maintaining data transfer pipelines to Google Cloud Storage.
  • Supporting data sharing integrations for analytics consumers.
  • Participating in breaking-change analysis of shared data schemas.
  • Contributing to internal tooling and operator-facing surfaces for data platform.
  • Deploying and maintaining workloads in Google Cloud Platform.
  • Implementing security remediations with senior engineer review.
  • Applying cloud-native secrets management patterns.
  • Writing secure code with parameterized queries and input validation.
  • Participating in white-box security reviews of internal services.
  • Documenting findings with specificity and reproduction steps.
  • Translating security findings into working code fixes with guidance.
  • Using AI coding assistants as a daily accelerator.
  • Generating and maintaining technical documentation with AI assistance.
  • Validating generated code against the actual codebase to avoid hallucinations.

Skills

Python
C#

Education

Bachelor's degree

Tools

GCS
REST APIs

Job description

When you join Verizon

You want more out of a career. A place to share your ideas freely - even if they're daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love - driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together - lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.

What You'll Be Doing:

You'll be a contributing member of the Data Services team that builds and maintains the MCP server infrastructure powering enterprise security data operations at Verizon - vulnerability data tooling, data transfers to Google Cloud Storage, analytics data sharing, and the pipelines and services that connect it all together.

You'll work on real services with real ownership - not in isolation, but alongside senior engineers who will help you build context and judgment. You're expected to complete assigned work end-to-end, ask the right questions when you're stuck, and grow your understanding of how the data platform fits together over time.

You're expected to actively use AI tools in your daily workflow. This team works that way by design, and we expect Engineer IIs to come in ready to learn and apply those capabilities as a productivity accelerator, not just a convenience.

Responsibilities include:
  • Contributing to the team's MCP server - building, maintaining, and extending MCP tools that expose vulnerability data and security datasets to AI agents and internal consumers.

  • Implementing feature work and bug fixes across data pipeline services under the direction of senior engineers - ingestion improvements, schema changes, and reliability work.

  • Building and maintaining data transfer pipelines to Google Cloud Storage - moving structured security data reliably between enterprise systems and GCS buckets.

  • Supporting data sharing integrations for analytics consumers - contributing to the services and exports that make security datasets available to downstream reporting and analytics platforms.

  • Participating in breaking-change analysis when shared data schemas or MCP tool contracts evolve: understand downstream impact and surface concerns to senior engineers.

  • Contributing to internal tooling and operator-facing surfaces where data platform capabilities are exposed - learning to think about what the consuming side needs, not just what the service provides.

  • Contributing to GCP-hosted services and infrastructure work - deploying and maintaining workloads in Google Cloud Platform as the team expands its cloud footprint.

  • Implementing security remediations identified through assessment, including application-layer vulnerability fixes and security configuration hardening, with senior engineer review.

  • Applying cloud-native secrets management patterns under guidance: Key Vault integration, Managed Identity, encrypted connections, and JWT validation.

  • Writing secure code by default - parameterized queries, input validation at system boundaries, least-privilege service accounts.

  • Participating in white-box security reviews of internal services - beginning to read code with an attacker's eye and learning to identify common application-layer vulnerabilities.

  • Contributing to documenting findings with specificity: file paths, line numbers, and reproduction steps under the direction of senior team members.

  • Translating security findings into working code fixes with senior engineer guidance on scope and remediation approach.

  • Using AI coding assistants as a daily accelerator - for navigating unfamiliar services, drafting code, and applying patterns across a codebase with senior review.

  • Generating and maintaining technical documentation with AI assistance - service overviews, data flow descriptions, and runbooks that help the next engineer.

  • Learning to validate generated code against the actual codebase, catch hallucinated APIs, and recognize when a suggestion needs to be overridden rather than shipped.

What We're Looking For

You're early in your career but past the very beginning. You take your work seriously - when you're assigned a service or a task, you dig in, ask smart questions, and see it through. You don't need someone to manage every step, but you know when to pull in senior eyes before making a call that's above your current context.

You take security hygiene seriously from the start - credential handling, input validation, least-privilege - and you apply those practices consistently, not just when someone's watching.

You're curious about how data moves - not just the pipeline stage you're working on, but where the data came from, where it ends up, and what breaks if your piece gets it wrong. That end-to-end thinking makes you easier to grow and more useful to the team early on.

You use AI tools the way the rest of this team does: as a real accelerator, not a shortcut. You're actively building habits around validating the output before it becomes someone else's problem.

You'll Need to Have:
  • Bachelor's degree or one or more years of relevant work experience.

  • One or more years of software engineering experience.

  • Working Python or .NET (C#) development skills - comfortable building and maintaining backend services, REST APIs, and data processing logic.

  • Familiarity with data pipeline concepts - understanding how data moves between systems, basic ETL patterns, and what can go wrong at each stage.

  • Understanding of common injection vulnerabilities and the importance of input validation and secure credential handling - especially relevant when working with vulnerability datasets

  • Exposure to cloud storage or data transfer patterns - GCS, S3, or similar object storage in a project or professional context.

  • Comfort reading unfamiliar code - you can follow data flow and find where the important logic lives even in codebases you didn't write.

  • Active or recent use of AI coding tools (Claude Code or similar) - not just awareness, but a genuine attempt to build them into how you work.

Even Better If You Have
  • Security+ or equivalent foundational security knowledge, or active pursuit of it

  • Awareness of OWASP Top 10 or OWASP API Security Top 10

  • Any exposure to SAST tooling or secrets scanning in a CI/CD pipeline

  • Hands-on experience with GCS - reading, writing, and managing objects; understanding bucket structure and IAM access patterns

  • Familiarity with analytics data sharing patterns - exports to BigQuery, Looker, Google Sheets, or similar platforms

  • Basic familiarity with JWT / OAuth 2.0 - understanding how tokens are issued and validated for service-to-service data access

  • Any exposure to MCP (Model Context Protocol) - understanding what MCP servers do and how tools are defined and consumed by AI agents

  • Hands-on experience with Google Cloud Platform (GCP) - Cloud Run, GCS, Pub/Sub, IAM, or related services

  • Any experience with Azure DevOps, GitLab, or similar CI/CD tooling

  • Familiarity with database patterns - query design, connection management, or migration tooling (EF Core or similar)

  • Some exposure to TypeScript or a JavaScript frontend framework (React, Angular, or similar)

  • Demonstrated genuine use of AI coding tools - can speak to what you've tried, where it helped, and where you learned it needed checking

  • Ability to write clear technical documentation that helps another engineer understand what you built and why

Where you'll be working

In this remote role, you'll work from home with occasional in-person trainings and meetings.

Scheduled Weekly Hours

40

Equal Employment Opportunity

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to veteran status, disability or other legally protected characteristics.

Benefits and Compensation
  • From health and wellness benefit options including: medical, dental, vision, short and long term disability, basic life insurance, supplemental life insurance, AD&D insurance, identity theft protection, pet insurance and group home & auto insurance.
  • We also offer a matched 401(k) savings plan, up to 8 company paid holidays per year and up to 6 personal days per year, paid parental leave, adoption assistance and tuition assistance, plus other incentives, we've got you covered with our award-winning total rewards package.
  • Depending on the role, employees have the opportunity to receive compensation in the form of premium pay such as overtime, shift differential, holiday pay, allowances, etc.
  • Newly hired employees receive up to 15 days of vacation per year, which grows with additional service.
  • For part-timers, your coverage will vary as you may be eligible for some of these benefits depending on your individual circumstances.

The salary will vary depending on your location and confirmed job-related skills and experience. This is an incentive based position with the potential to earn more. For part-time roles, your compensation will be adjusted to reflect your hours.

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