Diligent Corporation

Technology

TechnicalDirector,DataEngineering

CA$200–275k ~AI est. Vancouver, British Columbia, Canada Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Director candidates.

The Brief

“Technical Director, Data Engineering at Diligent Corporation. Skills: Data Engineering, AI Infrastructure, Distributed Systems. Design scalable data platforms. Build scalable data platforms”

What You'll Achieve.

Accelerate delivery of AI-native capabilities; Reduce infrastructure costs; Reduce operational complexity; Improve search performance; Improve ingestion performance; Improve retrieval performance; Improve search relevance; Improve ingestion relevance; Improve retrieval relevance; Teams adopt consistent patterns; Teams adopt maintainable patterns

Industry & Context.

Technology
Problems you'll solve

Debugging distributed systems; Troubleshooting; Root cause analysis

What They're Looking For.

Must Have

Significant real-world experience building and operating production systems, Hands-on engineering experience, Python strongly preferred, Experience with Java, Go, or TypeScript is a plus, Experience modernizing legacy platforms, Evolving architectures incrementally

Nice to Have

Experience with large-scale news, document, or regulatory data pipelines, Experience with search relevancy tuning, Exposure to governance, compliance, risk, or enterprise SaaS platforms, Familiarity with modern AI engineering workflows, Experience supporting startup-speed execution, Experience supporting enterprise-scale operations

What You'll Do.

Design scalable data platforms

Build scalable data platforms

Build distributed processing systems

Develop ingestion pipelines

Develop transformation pipelines

Develop retrieval pipelines

Build systems supporting AI/LLM applications

Build systems supporting semantic search

Build systems supporting RAG pipelines

Build systems supporting vector search

Build systems supporting agentic workflows

Implement production-grade solutions

Standardize infrastructure patterns

Improve observability

Improve cost efficiency

Partner with product teams

Partner with platform engineering teams

Drive pragmatic engineering decisions

Mentor engineers technically

Conduct design reviews

Provide architecture guidance

Perform pair debugging

Establish engineering standards

Establish CI/CD standards

Establish testing standards

Establish data quality standards

Establish monitoring standards

Establish operational excellence standards

How You'll Work.

Team & Collaboration

Work across large-scale pipelines; Work across search systems; Work across AI/LLM infrastructure; Work across event-driven architectures; Work across vector databases; Work across analytics platforms; Work across real-time data processing; Discuss high-level architecture; Work hands-on with engineering teams; Partner with product teams; Partner with platform engineering teams

Communication Scope

Discuss architecture

Process & Methodology

CI/CD, Agile

Full Job Description

Diligent is looking for a Technical Director of Data Engineering to help design and build the next generation of data and AI infrastructure powering our products and internal platforms. This is not a traditional management role. We are looking for an experienced builder; someone who still enjoys writing code, debugging distributed systems, evaluating frameworks, and getting hands-on with architecture and implementation. You will work across large-scale ingestion pipelines, search systems, AI/LLM infrastructure, event-driven architectures, vector databases, analytics platforms, and real-time data processing. You should be equally comfortable discussing high-level architecture with senior leadership and diving into a failing Kubernetes pod or optimizing a Spark job. The ideal candidate has strong opinions informed by real-world experience, understands tradeoffs deeply, and can move quickly without creating unnecessary complexity. What You’ll Do Design and build scalable data platforms and distributed processing systems Develop modern ingestion, transformation, and retrieval pipelines for structured and unstructured data Build systems supporting AI/LLM applications, semantic search, RAG pipelines, vector search, and agentic workflows Work hands-on with engineering teams to implement production-grade solutions rather than producing slideware Evaluate and standardize frameworks, tooling, and infrastructure patterns across teams Improve performance, reliability, observability, and cost efficiency of data systems Partner with product and platform engineering teams to accelerate delivery of AI-native capabilities Drive pragmatic engineering decisions balancing speed, maintainability, and operational simplicity Mentor engineers technically through design reviews, architecture guidance, and pair debugging Help establish engineering standards around CI/CD, testing, data quality, monitoring, and operational excellence What We’re Looking For Strong Hands-On Engineering Experienc

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