Java Web3 Jobs in North America

The Business Technology (BizTech) team at Chainalysis creates intuitive, scalable, and secure technology experiences that accelerate Chainalysis’ growth and empower our employees to do their best work.

The Sr. Data Engineer will design, build, and operate the data layer for our key business analytics, including the pipelines, data sets, and integrations necessary to deliver trusted business metrics and insights to our leaders and employees. They will connect our analytics stack with the rest of our infrastructure using both streaming and batch processes, and write and maintain ELTs and their orchestration in order to produce meaningful and timely insights. This work will be done in close partnership with Business Systems teams, our sibling Data Engineering team in R&D, and the BizOps Analytics team to build a system that has a sensible balance between data access and security, empowering analysts to support critical data-driven decisions across the company.

The ideal candidate will have experience working closely with Business Intelligence (BI) counterparts to empower business leaders and users with access to data that will help them make decisions. They have helped to develop a data architecture in past roles that balances access to data with security, and understand the full modern analytics stack. While they will leverage a shared data infrastructure, they have the background to enable them to contribute to forward-looking decisions around our overall company data infrastructure and architecture.

This role is open to remote candidates in the United States, with a preference for New York-based candidates who will join the team in our HQ either full-time or in a hub model.

In one year you’ll know you were successful if…

• You’ve worked with the BizOps Analytics team and our business stakeholders to understand their data lifecycle, the right integration points and helped them integrate analytics at the design stage of projects
• You have made an impact through reducing the time and manual overhead needed to relay insights to business leaders
• You have helped to build trust in our Business Data through the establishment of a data catalog, definition of a clear data architecture, and both the implementation and enforcement of policies around data security, handling, and retention
• You’ve developed and managed scalable data pipelines and build out new integrations with internal and external data sources
• You’ve maintained optimal data pipeline architecture, including looking for and proposing improvements to the existing architecture.
• Together with the rest of the team, you’ve evaluated our current analytics stack and are working towards a system that’s modern, scalable, maintainable and cost-effective.

A background like this helps:

• Experience leading efforts to implement Master Data Management (MDM), enterprise analytics in a SaaS company, and developing enterprise application integration strategies
• Experience in greenfield data engineering projects, specifically in analytics and data infrastructure projects.
• Advanced knowledge of modern data pipeline architecture and the AWS ecosystem including Redshift, Snowflake, Fivetran, Stitch, Databricks, Kafka, Airflow on Kubernetes and dbt
• Experience performing root cause analysis on data logging and ingestion processes, identifying opportunities to improve instrumentation and observability
• Comfort with Java or another JVM language
• Comfort writing SQL queries

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