Software Development Engineer - Data Acquisition & Normailization

Software Development Engineer - Data Acquisition & Normalization

Mountain View, California, United States

Company Overview

ID.me is the next-generation digital identity wallet that simplifies how individuals securely prove their identity online. Consumers can verify their identity with ID.me once and seamlessly login across websites without having to create a new login and verify their identity again. Over 152 million users experience streamlined login and identity verification with ID.me at 20 federal agencies, 45 state government agencies, and 70+ healthcare organizations. More than 600+ consumer brands use ID.me to verify communities and user segments to honor service and build more authentic relationships. ID.me's technology meets the federal standards for consumer authentication set by the Commerce Department and is approved as a NIST 800-63-3 IAL2 / AAL2 credential service provider by the Kantara Initiative. ID.me is committed to "No Identity Left Behind" to enable all people to have a secure digital identity.

Role Overview

ID.me is seeking a Software Development Engineer III to join the Data Acquisition & Normalization team. This team is responsible for building and operating the integrations that power the Identity Trust Graph — acquiring, normalizing, and refreshing identity attributes from authoritative and commercial sources.

In this role, you will contribute to building and maintaining connectors, data pipelines, and normalization services that ensure ID.me delivers reliable, real-time validation of identity attributes at internet scale. You will work alongside experienced engineers and partner with Product Managers from the Persons and Organizations teams to help translate validation contracts into working integrations.

This position is based in our Mountain View, CA office, 5 days per week.

Key Responsibilities

• Build and maintain connectors to government registries, telcos, licensing authorities, and commercial data providers.
• Standardize and reconcile heterogeneous data formats into clean schemas usable by the Identity Trust Graph.
• Monitor and help resolve upstream source changes; contribute to retries, fallbacks, and error handling to improve pipeline reliability.
• Contribute to the Attribute Validation Service (AVS) by adding trusted data that validates identity attributes against sources of record.
• Help deliver clean and validated attribute data to downstream consumers including Wallet, Fraud, and Domains.
• Assist in reporting coverage and freshness metrics to Product, Ops, and Analytics stakeholders.
• Handle sensitive data in accordance with NIST, ISO 27001, and FedRAMP standards.
• Write high-quality, maintainable, and well-tested code, including automated tests and observability instrumentation.
• Participate in system design discussions, code reviews, and technical documentation to support team alignment.

Key Success Metrics

• Attribute coverage and freshness SLA attainment.
• Connector uptime and reliability.
• Validation latency and success rates.
• MTTR (mean time to resolution) for broken integrations.
• Cost efficiency per validation event.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).
• 4+ years of experience developing web applications using OOP languages such as Java, Ruby, JavaScript, TypeScript, Go, Python, Rust, or C++.
• Exposure to data acquisition or integration work, including APIs, screen scraping, ETL, or normalization pipelines.
• Experience building systems in Docker, Kubernetes or Nomad and services in a containerized, cloud-based, infrastructure-as-code driven ecosystem such as GCP.
• Ability to deliver features end to end, including automated test coverage, observability, monitoring, and documentation.
• Ability to communicate technical tradeoffs clearly and work collaboratively within a team.
• Proficiency and strong interest in AI-assisted development tools (e.g., Claude Code or Codex) to accelerate delivery and code quality.

Preferred Qualifications

• Familiarity with operating data pipelines with reliability and SLA requirements.
• Understanding of distributed systems concepts, caching, asynchronous processing, and cloud-native patterns.
• Exposure to authentication and authorization standards (OAuth2, OIDC, JWT, or custom schemes).
• Familiarity with identity and credential verification systems, including data validation, proofing, or trust scoring.
• Exposure to event-driven architectures (Kafka, SNS/SQS) and patterns for decoupled service communication.
• Experience with cloud infrastructure (AWS, GCP, or Azure), including containerization and deployment pipelines.
• Familiarity with observability, monitoring, and incident response best practices.
• Awareness of compliance and security requirements for sensitive data (NIST, FedRAMP, ISO 27001).
• Bonus: Exposure to FinTech, identity, or data aggregation companies (e.g., Plaid, Yodlee, Envestnet).