Senior Data Engineer, Product Data Systems

🕒 September 21

🇦🇷 Argentina – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 18%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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BforeAI

WebsiteLinkedInAll Job Openings

51 - 200 employees

🔒 Cybersecurity

🤖 Artificial Intelligence

💸 Finance

💰 Non Equity Assistance on 2024-02

Cybersecurity • Artificial Intelligence • Finance

BforeAI is a cybersecurity company that specializes in predictive security solutions to prevent online threats before they impact businesses. They offer the PreCrime™ platform, which autonomously predicts, blocks, and preempts cyber threats such as phishing, spoofing, impersonation, hijacking, ransomware, online fraud, and exfiltration. Using behavioral analytics and advanced artificial intelligence, BforeAI monitors suspicious domain activity and provides actional disruption far in advance of conventional threat intelligence tools. They cater to various industries including financial, manufacturing, retail, and media, aiming to protect brands from financial and reputational harm. BforeAI’s solutions integrate seamlessly with existing security systems to disrupt malicious activity proactively and are recognized for their effectiveness by reports from Gartner, being a 2024 Gartner Cool Vendor for AI in Banking & Investment Services.

📋 Description

• 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 for the team • 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 for missing, delayed, duplicated, or inconsistent processing • Support safe replay and reprocessing without silently changing historical-result meaning • Preserve source evidence, provenance, lineage, processing context, and applicable versions • Define validation and quality controls at service boundaries and safely evolve schemas, contracts, and processing logic • Preserve tenant isolation while combining shared intelligence with customer-private evidence, configuration, and conclusions • Apply authorization, retention, deletion, audit, GDPR, and SOC 2 requirements throughout data-processing workflows • Evaluate managed services, open-source components, existing capabilities, and purpose-built services based on product and operational requirements • Contribute to architecture through working software, written proposals, prototypes, and technical review • Collaborate with Product, Platform Engineering, Threat Research, Data Science, Security, and customer-facing teams • Translate product requirements into technical contracts, communicate tradeoffs, and mentor engineers in modern data and distributed-systems practices

🎯 Requirements

• Significant hands-on experience building and operating data-intensive software for an externally used SaaS product • Strong software engineering specialization in data systems • Production development experience with Go, Scala, Rust, Java, or another comparable backend-service language • Willingness to work primarily in Go for pipeline and product data services • Proficiency with Python and SQL • Understanding of relational, document, graph, key-value, analytical, and object-storage models and their tradeoffs • Understanding of distributed-systems concerns including asynchronous processing, delivery semantics, concurrency, backpressure, idempotency, consistency, recovery, and failure isolation • Experience designing or operating event-driven systems using 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 • Ability to evaluate unfamiliar technologies based on engineering principles, communicate clearly, challenge weak assumptions constructively, and own delivery outcomes • Relevant experience in cybersecurity, threat intelligence, fraud, abuse prevention, or other evidence-intensive domains may help • Relevant experience with data provenance, explainability, auditability, or regulated data systems may help • Relevant experience with graph-based data processing, Neo4j, Azure Data Explorer, or Azure Data Lake Storage may help • Relevant experience with machine-learning feature pipelines, model inputs and outputs, or feedback and learning systems may help • Relevant experience migrating legacy batch or pipeline workloads into service-based, event-driven architectures may help • Relevant experience operating customer-facing data systems under defined reliability and recovery expectations may help • Must be authorized to work in the country where based; position is not eligible for visa sponsorship • Experience with every listed technology is not required

🏖️ Benefits

• Flexible time off • Sick days • All public holidays • Stock options • Location-independent work with a fully distributed team • Benefits tailored to the country where you will be working • Reasonable accommodations for qualified individuals with disabilities as needed

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