[Hiring] Senior Data Engineer @BforeAI

Role Description

BforeAI is hiring a Senior Data Engineer to build the production services and pipelines that acquire, normalize, enrich, relate, score, and deliver threat intelligence through BforeAI’s customer-facing SaaS product.

This is a hands-on product-engineering role. You will:

• Design systems and write production software for event-driven data processing.
• Build product data services:
  • Design, implement, test, deploy, and operate production services for ingestion, normalization, enrichment, identity resolution, scoring, and intelligence delivery.
  • Build maintainable pipeline workers, event consumers, APIs, scheduled processes, and supporting libraries.
  • Own the complete software lifecycle, including architecture, implementation, testing, deployment, monitoring, incident response, and improvement.
  • Establish reusable engineering patterns that other members of the team can follow.
• Engineer reliable event-driven pipelines:
  • Develop asynchronous workflows with explicit data, event, and work contracts.
  • Design for duplicate delivery, ordering constraints, idempotency, retries, timeouts, partial failure, dead-letter handling, backpressure, and recovery.
  • Make pipeline state and failures observable, with reconciliation that identifies missing, delayed, duplicated, or inconsistent processing.
  • Support safe replay and reprocessing without silently changing the meaning of historical results.
• Protect data integrity and tenant boundaries:
  • Preserve source evidence, provenance, lineage, processing context, and applicable versions from the first write.
  • Define validation and quality controls at service boundaries.
  • Preserve tenant isolation while safely combining shared intelligence with customer-private evidence, configuration, and conclusions.
  • Apply authorization, retention, deletion, audit, GDPR, and SOC 2 requirements throughout data-processing workflows.
• Shape the architecture and team:
  • Evaluate when to use a managed service, open-source component, existing capability, or purpose-built service based on product and operational requirements.
  • Contribute to architecture through working software, written proposals, prototypes, and constructive technical review.
  • Work with Product, Platform Engineering, Threat Research, Data Science, Security, and customer-facing teams.
  • Translate product requirements into clear technical contracts, communicate tradeoffs, and mentor engineers in modern data and distributed-systems practices.

Qualifications

• Significant hands-on experience building and operating data-intensive software for an externally used SaaS product.
• Strong software engineer specializing in data systems.
• Production development experience with:
  • Go, Scala, Rust, Java, or another comparable language used to build reliable backend services.
• Willingness to work primarily in Go for pipeline and product data services.
• Proficient with Python and SQL.
• Understanding of relational, document, graph, key-value, analytical, and object-storage models.
• Understanding of distributed-systems concerns.
• Experience designing or operating event-driven systems using technologies such as Kafka, Azure Event Hubs, AWS Kinesis, or comparable messaging infrastructure.
• Experience with containers, cloud infrastructure, automated testing, CI/CD, infrastructure automation, monitoring, and production operations.
• Ability to reason about provenance, replay, data quality, multi-tenant isolation, shared data, private customer context, and authorization boundaries.
• Evaluate unfamiliar technologies based on engineering principles.

Requirements

• Experience in cybersecurity, threat intelligence, fraud, abuse prevention, or other evidence-intensive domains is a plus.
• Experience with data provenance, explainability, auditability, or regulated data systems is a plus.
• Experience with graph-based data processing, Neo4j, Azure Data Explorer, or Azure Data Lake Storage is a plus.
• Experience with machine-learning feature pipelines, model inputs and outputs, or feedback and learning systems is a plus.
• Experience migrating legacy batch or pipeline workloads into service-based, event-driven architectures is a plus.
• Experience operating customer-facing data systems under defined reliability and recovery expectations is a plus.

Benefits

• Flexible time off.
• Sick days.
• All public holidays.
• Stock options.