The role
Wilkes & Liberty needs a Data / Intelligence Engineer who begins with the decision and works backward to the data. You will build pipelines, indexes, retrieval systems, and intelligence products that preserve source handling, quality, lineage, access rules, and uncertainty from collection through delivery. The goal is not another dashboard; it is a dependable product that operators can question, verify, and run inside their boundary.
What you will own
- Work with client operators to define the decisions, collection priorities, sources, handling constraints, freshness targets, quality measures, and dissemination rules for an engagement.
- Design and implement ingestion, normalization, enrichment, fusion, storage, indexing, retrieval, and delivery paths for structured and unstructured information.
- Engineer search and retrieval quality through explicit schemas, relevance tuning, filters and facets, language-aware analysis, evaluation sets, and observable failure cases.
- Build analytic and pattern-detection workflows that keep source provenance, assumptions, uncertainty, and operator review visible.
- Carry classification, need-to-know access, retention, lineage, and audit requirements through the pipeline instead of adding them only at the presentation layer.
- Monitor freshness, completeness, drift, query quality, and delivery thresholds; investigate broken or misleading outputs before they become operating decisions.
- Transfer the implemented system with versioned configuration, tests, data contracts, runbooks, known limits, and a prioritized expansion backlog.
- Partner with backend, infrastructure, security, and AI/agentic engineers while keeping pipeline and retrieval ownership distinct from model or agent orchestration.
What you bring
- You can design data pipelines and retrieval systems, not only write isolated transformations or dashboards.
- You work comfortably with SQL, programmatic data processing, APIs, batch or event-driven ingestion, schemas, indexes, and data contracts.
- You can define and measure data quality, provenance, lineage, freshness, and retrieval relevance.
- You understand access control and sensitive-data handling across collection, storage, indexing, analytics, and dissemination.
- You make uncertain or conflicting data visible rather than smoothing it into false precision.
- You can explain technical tradeoffs to analysts and operators and leave behind systems they can inspect and change.
Helpful experience
- Typesense, Solr, OpenSearch/Elasticsearch, or comparable search and retrieval systems.
- Python, TypeScript, Drupal/GraphQL content sources, relational databases, and mixed structured and unstructured corpora.
- Knowledge retrieval, retrieval evaluation, entity resolution, time-series or geospatial analysis, and analyst-facing workflows.
- Regulated or mission-oriented environments where data residency, need-to-know access, source handling, and auditability shape the architecture.
Equal opportunity and accommodations. Wilkes & Liberty considers qualified candidates without regard to protected characteristics. Reasonable accommodations are available during the application process.