Lead Cybersecurity - IAM Data Fabric SME
Location: Bangalore (Onsite 5 days/week) or should be willing to relocate to Bangalore or Hyderabad, collaboration with US team required.
Typical working hours: 1PM to 10 PM IST
About the Team
We are launching AT&T's greenfield Identity Data Fabric program—uniting human, machine, and all identities across the organization to create a single, comprehensive, attribute-rich profile trusted by any application and security control, in real time. We work at an enterprise scale with the latest in identity tech tools like Radiant Logic (IDDF/IDDM/IDA) and similar.
Role Summary
As a Lead Cybersecurity - IAM Data Fabric SME, you will drive the design, deployment, and enhancement of AT&T's internal identity aggregation and virtualization platform using leading-edge technology. Your focus will be on engineering robust pipelines and unified profiles, strengthening security and operational agility across the company.
What You'll Do
- Architect, implement, and maintain Radiant Logic (and comparable) solutions to aggregate and virtualize identity data across AT&T's internal hybrid cloud and on-premises environments.
- Build end-to-end batch, streaming, and event data pipelines for ingesting, correlating, and de-duplicating data from sources such as LDAP, AD, SCIM, REST, databases, and logs.
- Develop and publish unified global identity profiles, powering Zero Trust, IGA, and PAM programs, accessible via LDAP, REST, and Graph APIs.
- Solid understanding of Segregation of Duties (SOD), Data Feed Optimization and deep understanding of various data ingestion protocols and integration methods is necessary.
- Collaborate with IAM, PAM, HRIS, Cloud, and Application teams to analyze schemas, define SLAs, and automate data quality processes.
- Implement best practices for pipeline performance, reliability, and compliance (SOX, PCI, HIPAA); drive automation using CI/CD and Infrastructure-as-Code tools.
- Create and maintain dashboards and monitoring for data integrity, lineage, and freshness.
- Troubleshoot, debug, and optimize complex configurations and data flows; perform root cause analysis on identity-related issues.
- Continuously research new product features and conduct internal knowledge sharing to keep the team at the forefront of identity solutions.
What You Need to Bring
- 15+ years of data engineering or IAM data analytics experience, with recent work in large enterprise environments.
- Specialized, hands-on experience with Radiant Logic IDDF/IDDM/IDA (or similar platforms such as Strata.IO or Verna).
- Proven success in implementing large-scale ETL/ELT pipelines and identity correlation solutions.
- Expertise across IAM domains: IGA, PAM, RBAC/ABAC, MFA, directory services.
- Knowledge of identity protocols and APIs (LDAP, SCIM v2, REST/JSON, OAuth/OIDC, SAML).
- Strong data modeling ability (relational, graph, and document-based).
- Background in systems administration (Windows, Unix/Linux) and RDBMS (Oracle, SQL Server, MySQL).
- Scripting proficiency (Bash, PowerShell, Python); ability to read/debug Java scripts used in dataflows.
- Familiarity with CI/CD pipelines (e.g., Jenkins, GitHub Actions), IaC (Terraform, CloudFormation, ARM/Bicep), and containerized environments (Kubernetes, Docker).
- Excellent communication, documentation, and diagramming skills—be able to bridge conversations with technical teams and leadership.
Nice to Have
- Implementation or evaluation experience with Strata.IO, Verna, or similar identity data platforms.
- Familiarity with business application access control models (SAP, Workday, Salesforce, ServiceNow).
- Strong organizational, project management, and self-motivation skills.
- Familiarity with applying Artificial Intelligence (AI) or Machine Learning (ML) techniques in cybersecurity contexts (e.g., anomaly detection, threat hunting, behavioral analytics, or risk scoring).
- Experience leveraging AI-enabled tools (such as Copilot for Security, Darktrace, CrowdStrike Charlotte AI, or custom LLM integrations) to enhance detection, response, and automation workflows.
- Understanding LLM safety, prompt engineering, or AI governance frameworks (e.g., NIST AI RMF, EU AI Act readiness) is a plus.
- Exposure to data science fundamentals relevant to security (pattern recognition, supervised vs. unsupervised learning, model validation).
- Awareness of AI-driven risks (e.g., adversarial ML, data poisoning, model hallucination) and their mitigation within enterprise environments.
- Interest in leveraging GenAI for security operations, such as summarizing alerts, drafting reports, or automating incident triage
Why Join Us
- Be a key player in building the world's largest Identity Data Fabric, securing the backbone of AT&T.
- Access and contribute to the industry's most advanced identity platforms and tools.
- Collaborate directly with teams across India and the US on a strategic program that shapes AT&T's future.
