Senior Analytics Engineer

This is a fully remote position, open to applicants in Singapore.

📋 Description

• Take full ownership of analytics data pipelines from start to finish: design, construct, migrate, oversee, and maintain flows across source systems, data warehouses, Airflow, SQL transformations, and Metabase-facing datasets.

• Create reliable self-service data products: curated tables, views, semantic layers, metrics layers, and Metabase dashboards that teams can utilize without needing repeated custom analyses.

• Ensure data quality and observability: implement freshness checks, reconciliation checks, anomaly alerts, lineage documentation, pipeline health dashboards, and clear ownership for failures.

• Uphold high-value business analytics as a standard: include product activation and time-to-value (TTV), high-potential customer acquisition and retention, revenue and billing analytics, churn indicators, marketing funnel analytics, and executive dashboards.

• Assist teams in selecting and defining key metrics: facilitate the definitions of KPIs, formulas, ownership, and decision-making use cases without attempting to centrally manage every team’s metrics.

• Convert product and operational changes into analytics requirements: capture events, properties, logs, source tables, warehouse models, dashboard modifications, and validation criteria.

• Leverage AI-native workflows to accelerate processes: utilize AI coding assistants, model-centric programming (MCP), automated documentation, query generation, tests, and monitoring aids while ensuring outputs are reviewed and production-safe.

• Record the analytics system comprehensively: document source-of-truth definitions, data contracts, pipeline architecture, runbooks, dashboard ownership, and identified limitations.

• Handle unplanned analytics requests effectively: triage urgent data issues and transform recurring requests into sustainable datasets or dashboards.

⛳️ Requirements

• Over 5 years of experience in analytics engineering, data engineering, BI engineering, or data platform roles with responsibility for production analytics systems.

• Proficient in SQL: expertise in data modeling, warehouse transformations, query optimization, dependency analysis, and the design of reusable metrics and datasets.

• Strong Python skills: API extraction, automation, data validation, scripting, testing, and production-ready pipeline coding.

• Practical experience with workflow orchestration tools such as Airflow, including DAG design, task dependencies, retries, backfills, and operational debugging.

• Comprehensive understanding of data quality, lineage, observability, and incident-style responses to stale, broken, or inconsistent analytics data.

• Proficient in BI and dashboard creation, preferably using Metabase, with the ability to design dashboards that are intuitive, dependable, and aligned with decision-making.

• Solid understanding of SaaS, product, and business metrics: including funnels, activation, TTV, retention, cohorts, churn, revenue, Customer Acquisition Cost (CAC), Lifetime Value (LTV), and Net Revenue Retention (NRR).

• Comfortable working with operational data such as availability, incidents, latency, errors, and pipeline health, with the capacity to model and report it accurately in collaboration with engineering teams.

• Embrace an AI-native working approach: adept at using AI tools for coding, analysis, documentation, and automation while exercising strong judgment regarding validation and production safety.

• Excellent cross-functional communication skills: able to align both technical and non-technical teams on data definitions, trade-offs, ownership, and what should or should not be measured.

• Exceptional written and verbal communication skills in English.

• Familiarity with Web3 or blockchain domains is a plus.

• Experience with Customer Data Platforms (CDPs) and marketing analytics stacks, such as Segment.

• Experience with observability systems like Prometheus, Grafana, or ELK.

• Knowledge of dbt or similar transformation frameworks.

• Experience in developing lightweight internal tools or automating data workflows.

🏝️ Benefits

• Competitive salary in USD: We provide a transparent compensation structure that reflects your experience and contributions.

• Stock options: Participate in the company’s success as we continue to expand.

• Access to cutting-edge technology: Work with modern tools and stay up-to-date with industry trends.

• Flat organizational structure: Take initiative, act swiftly, and make decisions without unnecessary bureaucracy.

• Flexible working hours: Choose when you are most productive and maintain a healthy work-life balance.

• Engage in a rapidly growing global market: Contribute to a dynamic industry with tangible impact.

• Work within a multinational team: Collaborate with individuals from diverse backgrounds and perspectives.