Data Quality Engineer
LO:TECH is a capital markets firm for the onchain world, providing digital-asset market making, institutional-grade market data, analytics, and execution services. It serves institutional clients, trading firms, funds, banks, researchers, and token projects.
About LO:TECH
LO:TECH is a London-based trading business focused on onchain and digital-asset capital markets. Its proprietary high-frequency trading technology and infrastructure support liquidity provision across centralized and decentralized venues, agency execution algorithms, and institutional market-data services. The company provides live and historical tick-level crypto and prediction-market data through APIs, CSVs, websocket streams, and replay services, alongside transparent market-making dashboards and tailored enterprise data plans. Its clients include token projects, quantitative researchers, funds, banks, and other institutional market participants.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will own dashboards and quality controls for live and historical market data. You will define quality metrics, validate and reconcile data across venues, investigate anomalies, and automate checks. You will work with engineers to identify root causes, verify fixes, and report against service levels.
Requirements
- 2+ years in data quality, data analytics, QA, data operations, or data engineering
- SQL
- Python
- Experience building dashboards and visualisations for operational or data-quality monitoring
- Experience working with large datasets and comparing data across sources, time periods, and systems
- Command-line experience
Responsibilities
- Build and maintain data-quality dashboards
- Define data-quality metrics
- Validate and reconcile market data across CEX and DEX venues
- Investigate gaps, stale feeds, duplicates, schema changes, and unusual prices
- Build automated checks for live and historical data
- Identify root causes with engineering and verify fixes
- Report against service-level agreements for client-facing data
