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 • CanadaSenior💰 CA$130,000 - CA$180,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating data-intensive software for SaaS products, with a strong focus on Go programming, event-driven systems, and distributed systems design. Proficient in ensuring data quality, multi-tenant isolation, and compliance with regulatory requirements.

Highest-signal resume keywords

Go ProgrammingEvent-Driven Systems DesignData Quality ManagementDistributed Systems UnderstandingSaaS Product Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

GoScalaRustJavaPythonSQLKafkaAzure Event HubsAWS KinesisCI/CD

Soft Skills

Clear CommunicationMentoringConstructive Challenge

Tools & Technologies

ContainersCloud InfrastructureAutomated TestingMonitoringInfrastructure Automation

Industry Keywords

Data ProvenanceCybersecurityThreat IntelligenceRegulated Data SystemsEvidence-Intensive Domains

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
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
Evaluate managed services, open-source components, existing capabilities, and purpose-built services
Contribute to architecture through working software, 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

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; existing Go experience strongly preferred
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
Authorization to work in the country where based; position is not eligible for visa sponsorship
Helpful experience in cybersecurity, threat intelligence, fraud, abuse prevention, evidence-intensive domains, data provenance, explainability, auditability, regulated data systems, graph processing, Neo4j, Azure Data Explorer, Azure Data Lake Storage, machine-learning pipelines, legacy workload migration, or customer-facing data systems

Benefits

Comp & perks

Flexible time off
Sick days
All public holidays
Stock options
Benefits tailored to the country where you will be working
Reasonable accommodations for qualified individuals with disabilities as needed