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Data Engineer

VDart

 

United States

Posted On: 5 days ago
Experience: 5+ years
Availability: Onsite
Openings: 1
Category: Data Engineer
Tenure: Contract - Corp-to-Corp
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Description

  • Lead the architecture, design, and implementation of scalable, modular, and reusable data flow pipelines using Cribl, Vector, and other open-source platforms, ensuring consistent ingestion strategies across a complex, multi-source telemetry environment.
  • Develop platform-agnostic ingestion frameworks and template-driven architectures to enable reusable ingestion patterns, supporting a variety of input types (e.g., syslog, Kafka, HTTP, Event Hubs, Blob Storage) and output destinations (e.g., Snowflake, Splunk, ADX, Log Analytics, Anvilogic).
  • Spearhead the adoption of a schema normalization strategy, leveraging the Open Cybersecurity Schema Framework (OCSF), including field mapping, transformation templates, and schema validation logic—designed to be portable across ingestion platforms.
  • Design and implement custom data transformations and enrichments using scripting languages such as Groovy, Python, or JavaScript, while enforcing robust governance and security controls (SSL/TLS, client authentication, input validation, logging).
  • Ensure full end-to-end traceability and lineage of data across the ingestion, transformation, and storage lifecycle, including metadata tagging, correlation IDs, and change tracking for forensic and audit readiness.
  • Collaborate with observability and platform teams to integrate pipeline-level health monitoring, transformation failure logging, and anomaly detection mechanisms.
  • Oversee and validate data integration efforts, ensuring high-fidelity delivery into downstream analytics platforms and data stores, with minimal data loss, duplication, or transformation drift.
  • Lead technical working sessions to evaluate and recommend best-fit technologies, tools, and practices for managing structured and unstructured security telemetry data at scale.
  • Implement data transformation logic including filtering, enrichment, dynamic routing, and format conversions (e.g., JSON ↔ CSV, XML, Logfmt) to prepare data for downstream analytics platforms. (100 plus sources of data)
  • Contribute to and maintain a centralized documentation repository, including ingestion patterns, transformation libraries, naming standards, schema definitions, data governance procedures, and platform-specific integration details.
  • Coordinate with security, analytics, and platform teams to understand use cases and ensure pipeline logic supports threat detection, compliance, and data analytics requirements.

 

Experience Required:

•10+ Years of experience working in Cybersecurity

•5+ Years of experience on CRIBL/Vector/Datadog/Splunk or other data pipeline platforms

•5+ Years of experience on JavaScript, python, or other scripting language

Education

Bachelor's degree

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