Risk Labs
Analytics Engineer
NEWRemoteFull-timeGlobal
š Midš Remote
RemoteRemote work position availableActivePosted within the last 30 days
Job Description
[AI-summarized by JobStash]
You will be the direct owner of the transformation layer between raw ingestion and the clean data layer. You will audit, refactor, and migrate legacy models into a maintainable, well-documented system. You will design and run data quality frameworks with tests, alerts, and lineage and optimize BigQuery queries and materializations to control cost. You will build event data models and product observability to instrument new product launches and support analytics consumers. You will manage priorities, communicate proactively with stakeholders, and resolve production issues end-to-end.
Requirements
- āDeep expertise in data modelling across time horizons, dimensions, and granularities
- āAdvanced SQL with warehouse-aware, performant query design
- āProven experience owning a transformation layer in production and leading refactors or migrations
- āHands-on experience designing and implementing data quality frameworks including testing, alerting, and lineage
- āExperience with event data and product analytics tooling (Amplitude, Segment, or similar)
- āExperience with crypto data or highly normalized, irregular schemas and inherited complexity
- āStrong cross-functional communication with non-technical stakeholders
- āComfortable managing ambiguity and a shifting backlog
- āNice to have: experience with dbt
- āNice to have: familiarity with BigQuery partitioning, clustering, and materialization strategies
- āNice to have: practical use of AI/LLM tooling to accelerate workflows
Responsibilities
- āOwn the transformation layer between raw ingestion and the clean data layer
- āAudit, refactor, and migrate legacy models into maintainable pipelines
- āDesign and implement data quality frameworks including tests and alerting
- āImplement column-level lineage and codify business logic tests
- āOptimize BigQuery queries, storage, and materialization strategies
- āDesign event data models and product analytics instrumentation
- āCollaborate with Product and Analytics stakeholders to align priorities
- āRun and resolve production data incidents and root cause analysis
Benefits & Perks
- āTokens
- āEquity
- āPaid in stablecoins or fiat (candidate choice)
- āUnlimited vacation
- āFamily care support
- āTraining and development support
- ā100% remote
- āAt least two company-wide offsites per year
Tech Stack
LLMSQLPythoncost-optimizationproduct analyticsBigQuerydata qualitydata pipelineAmplitudedbt