Senior Analytics Engineer in London

This role offers the opportunity to build and scale the core analytics infrastructure powering decision-making across a fast-growing Web3 technology organization. You will design and own end-to-end data systems that transform raw operational, product, and business data into trusted insights used by teams across product, engineering, marketing, sales, and finance. Working in a highly technical, distributed environment, you will develop robust data pipelines, scalable datasets, and self-serve analytics products that enable data-driven decisions at every level. You will collaborate closely with leadership and cross-functional stakeholders to define key business metrics and ensure consistent, reliable reporting. This position blends data engineering, analytics engineering, and platform ownership in a high-impact, fast-paced environment. It is ideal for someone who thrives on building trusted data foundations that directly shape business strategy.

Accountabilities:

• Own and evolve end-to-end analytics data pipelines, including ingestion, transformation, orchestration, monitoring, and maintenance across warehouse and BI systems.
• Design and build scalable, self-serve data products such as curated datasets, semantic layers, metric definitions, and dashboards for cross-functional use.
• Implement strong data quality, observability, and reliability frameworks, including anomaly detection, lineage tracking, and pipeline health monitoring.
• Develop and maintain key business analytics covering product performance, growth, retention, revenue, churn, and marketing funnel metrics.
• Partner with stakeholders to define, structure, and standardize KPIs, ensuring alignment on metric definitions and business logic.
• Translate product, engineering, and operational changes into robust analytics models, data pipelines, and reporting structures.
• Document data systems, including architecture, definitions, ownership, and operational procedures to ensure transparency and maintainability.
• Triage and resolve ad hoc analytics issues while converting recurring needs into scalable, long-term data solutions.

Requirements:

• 5+ years of experience in analytics engineering, data engineering, BI engineering, or similar data platform roles with production system ownership.
• Advanced SQL expertise, including data modeling, transformation design, query optimization, and scalable dataset architecture.
• Strong Python skills for data pipelines, automation, API integration, testing, and workflow development.
• Hands-on experience with workflow orchestration tools such as Airflow, including DAG design, debugging, and operational maintenance.
• Deep understanding of data quality, observability, lineage, and incident management for analytics systems.
• Strong BI and dashboarding experience (preferably Metabase), with ability to design decision-driven, self-service analytics.
• Solid understanding of SaaS and digital business metrics such as funnels, retention, cohorts, CAC, LTV, and revenue analytics.
• Experience working with operational and engineering data such as system performance, logs, and reliability metrics.
• AI-native working approach, leveraging modern tools for coding, automation, and documentation with strong validation discipline.
• Excellent communication skills with the ability to align technical and non-technical stakeholders on data definitions and trade-offs.

Benefits:

• Competitive USD-based salary aligned with experience and impact.
• Stock options providing participation in company growth and success.
• Fully remote, flexible work environment with global collaboration.
• Flexible working hours focused on output and work-life balance.
• Opportunity to work on cutting-edge Web3 and blockchain infrastructure.
• Flat organizational structure enabling ownership, autonomy, and fast decision-making.
• Collaboration with a diverse, international team across multiple time zones.
• Access to modern tools and technologies in a rapidly evolving industry.