Identity and Access Management Data Engineer III

Capital Group

Data Engineer III managing identity and access management tasks at Capital Group. Analyzing data, enhancing security processes, and collaborating with teams for insights.

Posted 4/16/2026full-timeNew York City • California, New York, Texas • 🇺🇸 United StatesMid-LevelSenior💰 $141,648 - $240,248 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudCyber SecurityETLPythonSQLTableau

About the role

Key responsibilities & impact

Analyze IAM data to identify patterns, anomalies, and opportunities for improving access control policies and processes
Develop and maintain dashboards, reports, and visualizations to communicate IAM metrics and insights to stakeholders
Collaborate with IAM engineers and Operation and Governance teams to ensure data-driven decision-making aligns with organizational security policies
Utilize AI and machine learning tools to detect potential security risks, predict access-related issues, and automate IAM workflows
Support the design and implementation of scalable data pipelines for IAM data processing and integration
Stay updated on industry trends in IAM, data analytics, and AI to recommend innovative solutions.

Requirements

What you’ll need

Bachelor’s degree in computer science, Data Science, Information Security, or a related field (or equivalent experience)
5+ years of experience in data engineering and analysis, preferably within IAM or cybersecurity domains
Strong understanding of data engineering, with the ability to extract, transform, and load data from multiple sources (e.g., APIs, S3 buckets, cloud platforms like AWS, Databricks, Snowflake)
Proficiency in Python and SQL
Familiarity with cloud development patterns and source control (e.g., GitHub)
Proficient in IAM concepts (e.g., role-based access control, privileged access management, single sign-on)
Strong skills in data analysis tools and languages (e.g., Python, SQL)
Familiarity with data visualization tools (e.g., Tableau, Power BI)
Basic knowledge of data engineering practices, including ETL processes, data modeling, and pipeline development
Exposure to AI/ML frameworks or AI-driven analytics tools for predictive modeling or anomaly detection
Excellent problem-solving skills and attention to detail
Strong communication skills to collaborate with technical and non-technical stakeholders.

Benefits

Comp & perks

Generous time-away and health benefits from day one
Flexible work options
2-for-1 matching gifts for charitable contributions
Access to on-demand professional development resources
Retirement plan with company-funded contributions

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Hard Skills & Tools

data engineeringdata analysisPythonSQLETL processesdata modelingpipeline developmentAImachine learningdata visualization

Soft Skills

problem-solvingattention to detailcommunication