Onsite job opportunity for the role of Mid-level Data Engineer in Mountain View, CA (Onsite)

[Rahul Pandey]

Greetings,

This is Rahul from Quantum world Technologies; I am working as Senior Technical Recruiter in this company. I have an Onsite Job Opportunity with one of our clients. Please share your resume if you are interested in the job details given below:

Job Title: Mid-level Data Engineer

Location : Mountain View, CA (Onsite)

Pipeline Development & Data Ingestion

• Design, build, and maintain scalable ingestion pipelines from diverse data sources including UEBA/DLP tools, Workday (HR lifecycle events), AWS, GitHub, and GenAI monitoring platforms (e.g., Aim Security)
• Process structured and semi-structured event data including user behavior logs, access events, DLP alerts, shipment scans, and endpoint telemetry
• Implement incremental and near-real-time load patterns to support time-sensitive security analytics and alert triage

Data Modeling & Warehouse Architecture

• Build and maintain dimensional data models (fact/dimension) that correlate employee identity, behavioral signals, and security events across business units
• Design schemas that support persona-based risk views (onboarding/offboarding, privileged users, non-human identities)
• Ensure data models are optimized for downstream BI consumption (dashboards, KPI reporting)

Identity & Access Data Engineering

• Build pipelines to ingest and correlate Non-Human Identity (NHI) data — service accounts, bots, API keys — from AWS, GitHub, and internal data lakes
• Develop risk-scoring data frameworks that flag orphaned accounts, anomalous NHI behavior, and privileged access escalation events
• Integrate Workday employee lifecycle data to correlate HR events (resignations, transfers, onboarding) with security signals

DLP & GenAI Data Integration

• Ingest and normalize telemetry from DLP platforms tracking data egress (personal GitHub uploads, cloud storage misuse, USB activity, mass downloads)
• Build pipelines from GenAI monitoring tools to capture unauthorized LLM usage and sensitive data (PII/IP) exposure in AI prompts
• Correlate unauthorized software installs and malicious web activity signals as potential insider threat precursors

Data Quality & Governance

• Implement robust data validation, reconciliation, and quality controls across all ingestion pipelines
• Ensure audit-ready data lineage and traceability supporting compliance, legal, and HR review workflows
• Apply access controls and data governance standards appropriate for sensitive security and HR data

 

Required Qualifications

• Strong proficiency in SQL and at least one scripting language (Python or PySpark)
• Proven experience with AWS data services: Glue, S3, Redshift, Athena, Lambda, Kinesis, Step Functions
• Experience ingesting data from APIs, SaaS platforms, and HR systems (Workday experience is a strong plus)
• Solid understanding of data modeling — star/snowflake schemas, dimensional design, slowly changing dimensions
• Experience with AWS data orchestration tools (e.g., AWS Step Functions, AWS MWAA, AWS Glue Workflows, or equivalent)
• Experience with streaming or near-real-time pipelines (Kinesis, Kafka, or equivalent)
• Familiarity with data quality frameworks and implementing validation/reconciliation logic
• Comfortable working with sensitive, access-controlled datasets and applying appropriate security controls

Preferred Qualifications

• Experience in a security, fraud, or risk analytics environment
• Experience with Non-Human Identity (NHI) data — service accounts, bots, API keys across AWS/GitHub
• Knowledge of Workday data and employee lifecycle event modeling
• Hands-on experience with multiple AWS orchestration services (Step Functions, MWAA, Glue Workflows)
• Exposure to GenAI governance tooling or endpoint telemetry platforms

Familiarity with Row-Level Security (RLS) and attribute-based access controls in data platforms

 

 

Thanks & Regards

Rahul Pandey

rahul....@quantumworldit.com