Senior Data Engineer

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Consensys is the leading blockchain and web3 software company founded by Joe Lubin, CEO of Consensys and Co-Founder of Ethereum. Since 2014, Consensys has been at the forefront of innovation, pioneering technological developments within the web3 ecosystem.

Through our product suite, including the Meta Mask platform, Infura, Linea, Diligence, and our NFT toolkit Phosphor, we have become the trusted collaborator for users, creators, and developers on their path to build and belong in the world they want to see.

Whether building a dapp, an NFT collection, a portfolio, or a better future, the instinct to build is universal. Consensys inspires and champions the builder instinct in everyone by making web3 universally easy to use and develop on.

Our mission is to unlock the collaborative power of communities by making the decentralized web universally easy to access, use, and build on.

You’ll get to work on the tools, infrastructure, and apps that scale these platforms to onboard one billion participants and 5 million developers. You’ll be constantly exposed to new concepts, ideas, and frameworks from your peers, and as you work on different projects — challenging you to stay at the top of your game. You’ll join a network of builders that reaches the edge of our ecosystem.

Consensys alumni have moved on to become tech entrepreneurs, CEOs, and team leads at tech companies.

The Data team sits within the Office of the COO and builds the infrastructure that powers analysis across the organisation. We design, run, and optimise pipelines that bring together product, marketing, and financial data  role is to ensure data is reliable, accessible, and ready for usehelping Consensys move fast while maintaining quality and trust.

• 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.

• 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, Big Query, 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.: Data Hub).
• 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.: Git Hub Actions).
• A collaborative mindset and eagerness to work with both technical and non-technical colleagues.

Don't meet all the requirements? Don't sweat it. We’re passionate about building a diverse team of humans and as such, if you think you've got what it takes for our chaotic-but-fun, remote-friendly, start-up environment—apply…