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About the role
Trust Wallet is the leading non-custodial cryptocurrency wallet, trusted by over 200 million people worldwide to securely manage and grow their digital assets. With support for over 10 million assets across 100+ blockchains, Trust Wallet offers a seamless, multi-chain experience backed by industry-leading self-custody technology, a vibrant community, and a growing ecosystem of partners.
We are recruiting a Senior Data Engineer to play a key role in building and scaling the data platform that powers analytics across Trust Wallet. You will design, develop and maintain data pipelines and data models, ensuring a seamless, scalable and reliable flow of data from source systems through to the decisions it supports. Leveraging Databricks and Spark across streaming and batch workloads, dbt or a similar transformation framework, cloud infrastructure, and custom solutions in Python, you will work closely with data analysts and engineering teams to turn data into a strategic asset.
This is a full-time, remote position.
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Preferred Skills
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Responsibilities
- Data Platform Engineering: Architect and maintain robust, scalable and secure data infrastructure on Databricks, covering both streaming and batch workloads.
- Data Pipeline Development: Design, develop and maintain data pipelines, primarily in Python and Spark, to automate ingestion and transformation across internal systems, external providers and on-chain sources.
- Data Modelling: Design and maintain dimensional data models and transformation layers in dbt, with tests and documented contracts, so metrics are consistent and reusable across the company.
- Data Lake Management: Oversee the data lake and lakehouse layers, ensuring efficient storage, effective partitioning, high data quality, and monitoring and alerting that surfaces issues early.
- Integration and Customisation: Integrate Databricks with a wide range of data sources, including change data capture from operational databases, third-party APIs and blockchain data, and adapt data flows to specific business needs.
- Performance, Scalability and Cost: Optimise pipelines and storage for performance, reliability and cost efficiency at scale.
- Data Governance and Security: Apply best practices for governance, security and compliance in cloud and Databricks environments, including access control, encryption and monitoring.
- Collaboration and Documentation: Work closely with platform engineers, data analysts and other stakeholders to understand data requirements, and document infrastructure, models and best practices.
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