Senior Data 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 robust data pipelines that integrate sources across the business. • Collaborate closely with analysts, business stakeholders, and other engineering teams to gather requirements, align timelines, discuss architecture, and ensure successful delivery. • Document data pipelines, best practices, and processes to support onboarding and knowledge sharing within the team. • Develop and optimize data models to deliver trusted, structured, and business-ready data. • Ensure data quality, security, and governance are embedded in all pipelines and systems. • Orchestrate and monitor pipeline execution to ensure reliability and scalability. • Deploy and manage infrastructure as code. • Build and tune big data pipelines using SQL, Python, and distributed processing frameworks. • Work with cloud data warehouses to enable insights and analytics. • Maintain and update reporting solutions and user dashboards. • Automate workflows and improve CI/CD pipelines to reduce manual processes.

🎯 Requirements

• Over 6 years of experience as a Data Engineer • Use Trusted Execution Environments (TEEs) to securely process sensitive user data, ensuring it remains protected and only aggregated insights are released. • Strong SQL skills and experience with cloud warehouses (e.g.: Snowflake, BigQuery, Redshift). • Hands-on experience with transformation and orchestration tools (e.g.: dbt, Airflow, Dagster). • Comfort with Python or other scripting languages for ETL and automation. • Familiarity with data governance and metadata management (e.g.: DataHub). • Experience deploying and managing infrastructure as code (e.g.: Terraform, Pulumi). • Exposure to data integration and ingestion tools (e.g.: Airbyte, Segment). • Experience with big data and distributed processing (e.g.: Apache Spark, AWS EMR, S3). • Exposure to open source projects • Experience maintaining and improving reporting solutions and dashboards (e.g.: Preset/Superset, Cube.dev). • Familiarity with CI/CD practices and automation (e.g.: GitHub Actions). • A collaborative mindset and eagerness to work with both technical and non-technical colleagues.