Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
Scoutfield Logo

See all jobs on Scoutfield

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
BforeAI

Senior Data Engineer, Product Data Systems

BforeAI

. Design, implement, test, deploy, and operate production services for ingestion, normalization, enrichment, identity resolution, scoring, and intelligence delivery .

Posted 9/21/2026full-timeRemote • ArgentinaSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and operating data-intensive software, particularly in SaaS environments, with a strong focus on distributed systems, data processing, and event-driven architectures. Proficient in programming languages such as Go, Python, and SQL, while ensuring compliance with data governance and security standards.

Highest-signal resume keywords
Data-Intensive Software DevelopmentGo Programming LanguageEvent-Driven Systems DesignDistributed Systems ExpertiseData Governance Compliance

ATS Keywords

Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Go ProgrammingPython ProgrammingSQL ProficiencyEvent-Driven ArchitectureData ProcessingAsynchronous ProcessingData Quality ControlDistributed SystemsData ProvenanceGraph-Based Data Processing
Soft Skills
Clear CommunicationConstructive ChallengeMentoring Engineers
Tools & Technologies
KafkaAzure Event HubsAWS KinesisCI/CDContainersCloud InfrastructureAutomated TestingMonitoring ToolsInfrastructure AutomationData Lake Storage
Industry Keywords
SaaS ProductCybersecurityThreat IntelligenceFraud PreventionRegulated Data SystemsAuditabilityMulti-Tenant IsolationData QualityReliability ExpectationsService-Based Architecture

Tech Stack

Tools & technologies
AWSAzureCloudCyber SecurityJavaKafkaNeo4jPythonRustScalaSQLGo

About the role

Key responsibilities & impact
  • 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

What you’ll need
  • 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

Comp & perks
  • 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