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Architect · 7+ years exp
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Fusemachines provides artificial intelligence products and engineering talent. Its teams build machine learning systems for enterprise clients. The company also runs an artificial intelligence education programme.

About Fusemachines

Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, United States, Canada, and Dominican Republic and more than 400 employees). Fusemachines seeks to bring its global expertise in AI to transform companies around the world.

Remote (US or Canada)

Seeking a hands-on Senior Security Data Solution Architect with 7+ years of experience designing and implementing large-scale security data and analytics solutions within the financial services industry. The ideal candidate possesses deep security domain fluency, expertise in ingesting, normalizing, and standardizing security telemetry and SIEM logging, and a strong understanding of Databricks alongside Snowflake on AWS. Must have proven experience in data architecture leadership, business continuity, disaster recovery, high availability, and modern AI/agentic integration capabilities.

Responsibilities:

  • Architect end-to-end security data solutions on AWS, utilizing Databricks and Snowflake to integrate, normalize, and standardize disparate security telemetry and SIEM logs.
  • Translate functional and non-functional security requirements into scalable data models, low-level designs, and standardized architectural artifacts.
  • Provide technical leadership to build queryable, sustainable data storage layers that move away from BI-heavy dependencies and answer critical operational and risk metrics for the security leadership team.
  • Guide and mentor data engineers and analysts on data modeling, pipeline development, and data architecture best practices.
  • Design data governance solutions including metadata management, data cataloging, quality framework enforcement, and lineage tracking across security domain datasets.
  • Evaluate and integrate AI/ML services and natural language interrogation layers (such as LLMs and agentic development tools) to streamline security incident analysis and bespoke data queries.
  • Design highly available, scalable, and resilient data solutions, including disaster recovery and business continuity plans.
  • Collaborate with cross-functional security, risk, and product management teams in an Agile environment.

Qualifications:

  • Bachelor's degree in Computer Science, Information Security, or a related field.
  • 7+ years of data architecture and hands-on engineering experience with a strong focus on security datasets and risk analytics in the financial industry.
  • Deep expertise in security telemetry normalization, data integration, and SIEM (Security Information and Event Management) logging platforms.
  • Hands-on experience with Databricks and Snowflake architectures, PySpark/Spark, SQL, data lakes/lakehouses, ELT/ETL pipelines, and stream processing tools (e.g., Kafka).
  • Strong practical understanding of AWS cloud infrastructure and security tools.
  • Familiarity with AI/ML services, LLMs, and agentic workflows for automated analytics.
  • Strong understanding of SDLC, Agile methodology, and DevOps/DataOps principles.
  • Excellent communication and leadership skills with the ability to translate technical security requirements into strategic data architectures.

Preferred Certifications:

  • Databricks Certifications: Databricks Certified Data Engineer Professional or Databricks Certified Solutions Architect.
  • Snowflake Certifications: SnowPro Core or SnowPro Advanced Architect.
  • Cloud Certifications: AWS Certified Data Engineer - Associate or AWS Certified Solutions Architect - Professional.
  • Security Certifications: Certified Information Systems Security Professional (CISSP), Certified Cloud Security Professional (CCSP), or CompTIA Security+.

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

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