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Member of Technical Staff, Reporting & Statements (Data Engineer)
United States
Engineering â Data Engineering /
Full-Time - Remote /
Remote
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At Anchorage Digital, we are building the worldâs most advanced digital asset platform for institutions to participate in crypto.
Founded in 2017, Anchorage Digital is a regulated crypto platform that provides institutions with integrated financial services and infrastructure solutions. With the first federally chartered crypto bank in the US, Anchorage Digital offers institutions an unparalleled combination of secure custody, regulatory compliance, product breadth, and client service. Weâre looking to diversify our team with people who are humble, creative, and eager to learn.
We are a remote friendly, global team, but provide the option of working in-office in New York City, Sioux Falls, Porto, Lisbon, and Singapore. For our colleagues not located near our beautiful offices, we encourage and sponsor quarterly in-person collaboration days to work together and further deepen our Village.
Join us as a founding engineer on our Reporting & Statements team. You'll design the systems that power every financial report and statement we deliver from monthly reports to daily statements to custom client requests. We're building automated frameworks that guarantee accuracy and consistency for every number we send to clients.
We have created the Factors of Growth & Impact to help Villagers better measure impact and articulate coaching, feedback, and the rich and rewarding learning that happens while exploring, developing, and mastering the capabilities and contributions within and outside of the Asset Data role:
Technical Skills:
- Evolve our architecture from decentralized reporting scripts to a centralized, framework-based delivery system
- Build automated validation and reconciliation that lets us scale without adding manual oversight
Complexity and Impact of Work:
- Design data models that become a trusted, shared source of truth for downstream product teams and external APIs
- Navigate complexity across multiple product data streams, applying consistent logic to all financial statements
Organizational Knowledge:
- Work with Product and Foundations teams to standardize how we capture and represent financial data
- Create self-service frameworks so other teams can add new report types through configuration instead of code
Communication and Influence:
- Listen to product stakeholders to stay ahead of scaling needs for client-facing data
- Help mature our engineering culture by advocating for and modeling "Data as a Product" principles and high-quality engineering standards
You may be a fit for this role if you:
- 7+ years building data systems: You have experience creating internal tools, frameworks, or engines that handle 10x scale
- Financial domain experience: You've worked in fintech, banking, or other environments where numbers matter. You understand what a "Statement of Record" means and the precision it demands.
- Systems thinking: You consider the next 100 products, not just the current one. You value extensible systems over one-off pipelines.
- Solid technical foundation: You're proficient with Python (Pandas/Polars/Arrow) and SQL, with experience in BigQuery or similar cloud warehouses and modern orchestration tools like Airflow or Dagster.
Although not a requirement, bonus points if:
- You've been a data consumer: Prior experience as a financial or business analyst gives you the perspective to design truly usable data models.
- You care about performance: You enjoy making data move faster and cheaper, whether through ADBC, multiprocessing, vectorized operations, or other optimizations.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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What does a data scientist in web3 do?
A data scientist in web3 is a type of data scientist who focuses on working with data related to the development of web-based technologies and applications that are part of the larger web3 ecosystem
This can include working with data from decentralized applications (DApps), blockchain networks, and other types of distributed and decentralized systems
In general, a data scientist in web3 is responsible for using data analysis and machine learning techniques to help organizations and individuals understand, interpret, and make decisions based on the data generated by these systems
Some specific tasks that a data scientist in web3 might be involved in include developing predictive models, conducting research, and creating data visualizations.