Senior Data Engineer

The Opportunity

As a Data Engineer, you will play a key role in shaping the data infrastructure that powers our AWS-based data lake. You’ll design, deploy, and maintain data pipelines to ensure a seamless, scalable, and reliable flow of information that underpins our analytics and decision-making.

By leveraging your expertise with AWS, Databricks, Airbyte (or similar ELT/ETL tools), and custom solutions in Python or Go, you’ll collaborate closely with our team to transform raw data into a strategic asset for the company.

Responsibilities

• Data Infrastructure Setup: Architect and maintain robust, scalable, and secure data infrastructure on AWS leveraging Databricks.
• Data Pipeline Development: Design, develop, and maintain data pipelines, primarily using tools like Airbyte and custom-built services in Go, to automate data ingestion and ETL processes.
• Data Lake Management: Oversee the creation and maintenance of the data lake, ensuring efficient storage, high data quality, and effective partitioning, organization, performance, monitoring and alerting.
• Integration and Customization: Integrate tools like Airbyte with various data sources and customize data flows to align with specific business needs. Where necessary, build custom connectors in Go to support unique data requirements.
• Performance and Scalability: Optimize data pipelines and data lake storage for performance and scalability, ensuring low latency and high availability.
• Data Governance and Security: Implement best practices for data governance, security, and compliance in AWS and Databricks, 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, processes, and best practices.

Qualifications

• Experience in Data Engineering: 3+ years of experience as a Data Engineer, with a focus on data lake architecture and ETL pipeline development.
• AWS Proficiency: Strong experience with Databricks and AWS services including but not limited to S3, Glue, Lambda, Redshift, and IAM.
• ETL Expertise: Hands-on experience with Airbyte or similar ETL tools for data ingestion and transformation.
• Proficiency in Python/Go: Experience writing services and connectors in Python/Go, particularly for data pipeline automation.
• SQL and Data Modeling: Solid understanding of data modeling, SQL, and database concepts.
• Data Governance and Security: Experience implementing security and governance best practices in cloud environments.

Working at Trust Wallet

• Do something meaningful; Be a part of the future of finance technology and the no.1 company in the industry
• Fast moving, challenging and unique business problems
• International work environment, flat organization, flexible working hours
• Great career development opportunities in a growing compan