Senior Analytics Engineer

Job not on LinkedIn

October 23

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MetaMask

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Crypto • Web 3 • Fintech

MetaMask is a leading self-custodial crypto wallet that serves as a gateway to blockchain applications. Available as a browser extension and mobile app, it enables users to track and manage their web3 assets securely and conveniently. With features such as buying, selling, staking, and bridging crypto tokens, MetaMask empowers over 100 million users worldwide to control their digital assets and interact on the decentralized web with privacy and security.

51 - 200 employees

Founded 2016

₿ Crypto

🌐 Web 3

💳 Fintech

📋 Description

• Design, build, and maintain reliable data models that transform raw data into business-ready datasets. • Collaborate closely with analysts, data scientists, and business stakeholders to understand requirements and translate them into actionable metrics, KPIs, and dashboards. • Develop and maintain metrics definitions, semantic layers, and data documentation to ensure consistency across teams. • Build, optimize, and test dbt models to deliver clean, reliable, and trusted data. • Ensure data quality, accuracy, and governance are embedded in all models and pipelines. • Create dashboards, reports, and visualizations that empower business users to make data-driven decisions. • Work with SQL and transformation frameworks to write efficient queries and maintain performant models. • Partner with data engineers to ensure smooth data ingestion and availability for analytics. • Continuously improve processes and workflows to increase efficiency, reliability, and scalability.

🎯 Requirements

• Over 6 years of experience as a Analytics Engineer • Previous experience developing and tracking KPIs for public companies • Expert-level SQL skills with experience writing complex queries and optimizing performance. • Hands-on experience with dbt for data transformation and modeling. • Strong understanding of data modeling concepts (e.g., star schema, snowflake schema, dimensional modeling). • Familiarity with BI and dashboarding tools (e.g., Looker, Superset, Tableau, Power BI). • Experience defining KPIs and metrics for business stakeholders. • Comfort with Python or other scripting languages for lightweight data transformations and automation. • Knowledge of data governance, lineage, and documentation tools (e.g., DataHub, Great Expectations). • Understanding of cloud data warehouses (e.g., Snowflake, BigQuery, Redshift). • Collaborative mindset and ability to work closely with both technical and non-technical stakeholders. • Experience with version control and CI/CD practices in analytics workflows (e.g., GitHub Actions).