Data Ingestion at Scale: Design, build, and operate pipelines that ingest large volumes of telemetry from mobile endpoints reliably and efficiently.
ETL & Detection Pipelines: Build and maintain the ETL processes that transform raw data, and implement the detection logic that runs across it to surface threats.
Forensic Artefact Extraction: Architect the extraction and parsing of complex data from mobile forensic artefacts, handling the varied and often undocumented structures these artefacts contain.
Partnering with Research: Work closely with the research team to implement their prototypes in production, translate their detection ideas into robust pipeline logic, and build the data access and tooling they need to uncover mobile spyware.
Scalability & Reliability: Ensure the data platform performs at scale, optimizing throughput, query performance, and cost across large datasets, with strong reliability and fault tolerance.
Data Quality & Observability: Build monitoring, validation, and error-handling into the pipelines so data issues are caught early and the system is observable end to end.
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Build and maintain high-volume ingestion and ETL pipelines in Python
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Implement and productionize detection logic from research prototypes
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Design parsers and extraction logic for complex mobile forensic artefacts,
accommodating evolving data formats and schema changes
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Optimize data storage and query performance across large datasets
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Deploy and operate services on AWS Fargate, EC2, and Serverless
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Collaborate directly with researchers to understand what they need and build it
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Establish monitoring, alerting and data quality checks to detect issues and
ensure pipeline reliability
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Contribute to architectural decisions on how data flows through the platform