Analytics Engineer

Unchain Data; United States; Remote; USD 130,000 - 210,000; Full time

Benefits offered by this job

Salary in tokens & equity

Paid in stablecoins or fiat

Unlimited vacation

100% remote

Company offsites

Job summary

Risk Labs, the foundation behind UMA and Across, is seeking an Analytics Engineer to own the transformation layer within Data Engineering. You’ll collaborate with the Platform Engineering Lead and Data Analytics Lead in a remote-first, globally distributed team to push crypto data infrastructure forward.

You’ll design data models, ensure data quality, optimize BigQuery costs, and build robust event data across the product suite, using dbt, BigQuery, Python, Airflow, Amplitude, and Segment.

Qualifications

• Deep expertise in data modelling across multiple time horizons, dimensions, and levels of granularity.
• Advanced SQL: performant, readable, and warehouse-aware.
• Experience owning a transformation layer in production, including a meaningful refactor or migration.
• Hands-on experience designing and implementing data quality frameworks: testing, alerting, and lineage.
• Experience with event data and product analytics tooling (Amplitude, Segment, or similar).
• Experience with crypto data environments characterised by high normalisation and irregular schemas.

Responsibilities

• The Transformation Layer — DRI for everything between raw ingestion and the clean data layer. Own the modelling strategy.
• Refactor and Legacy Migration — Audit, cut redundancy, and rebuild into something clean, traceable, and maintainable.
• Data Quality and Testing — Design and own the approach to data quality: testing, alerting, and column-level lineage.
• BigQuery Cost Optimisation — Own query and storage efficiency, refactor materialisation strategies to reduce unnecessary spend.
• Event Data and Product Observability — Build a robust event data model that gives meaningful observability across the full product suite.

Skills

Data modelling

Advanced SQL

Transformation layer

Data quality frameworks

Event data analytics

Crypto data environments

Tools

Amplitude

Segment

dbt

BigQuery

Python

Airflow

Job description

Who is Risk Labs?

Risk Labs is the foundation and core team behind UMA and Across — decentralised protocols governed by community members across the globe. UMA's optimistic oracle (OO) can record any verifiable truth or data onto a blockchain. Across is leading the future of interoperability with its frontier intents-based architecture.

We are a remote-first, globally distributed team focused on building infrastructure that pushes crypto forward.

Why This Role Exists

This is the first analytics engineering role at Risk Labs. The transformation layer has reached a level of complexity that demands a dedicated owner. You'll sit within Data Engineering, reporting to the Platform Engineering Lead, and work most closely with the Data Analytics Lead and Product team.

We are serious about building a truly agentic data platform, and this hire is a prerequisite for that. Agentic systems are only as good as the data they run on.

What You'll Own

• The Transformation Layer — DRI for everything between raw ingestion and the clean data layer. Own the modelling strategy.

• Refactor and Legacy Migration — Audit, cut redundancy, and rebuild into something clean, traceable, and maintainable.

• Data Quality and Testing — Design and own the approach to data quality: testing, alerting, and column-level lineage.

• BigQuery Cost Optimisation — Own query and storage efficiency, refactor materialisation strategies to reduce unnecessary spend.

• Event Data and Product Observability — Build a robust event data model that gives meaningful observability across the full product suite.

Skills and Experience

Required

• Deep expertise in data modelling across multiple time horizons, dimensions, and levels of granularity

• Advanced SQL: performant, readable, and warehouse-aware

• Experience owning a transformation layer in production, including a meaningful refactor or migration

• Hands-on experience designing and implementing data quality frameworks: testing, alerting, and lineage

• Experience with event data and product analytics tooling (Amplitude, Segment, or similar)

• Experience with crypto data environments characterised by high normalisation and irregular schemas

Nice to Have

• Experience with dbt

• Familiarity with BigQuery: query optimisation, partitioning, clustering, materialisation strategies

• Practical use of AI/LLM tooling to accelerate workflows

Tech Stack

BigQuery, dbt, Python, Airflow, Amplitude, Preset/Superset, Hex, GCP (Cloud Run, Cloud Build, Cloud Functions, Datastream)

Compensation and Benefits

• Competitive salary with mix of salary, tokens, and equity

• Paid in stablecoins or fiat, your choice

• Unlimited vacation — and they actually take it

• 100% remote

• At least two company-wide offsites per year

• Family care, training, and development support