Data & Reporting Architect

At Anchorage Digital, we are building the world’s most advanced digital asset platform for institutions to participate in crypto. Anchorage Digital is a crypto platform that enables institutions to participate in digital assets through custody, staking, trading, governance, settlement, and the industry’s leading security infrastructure. Home to Anchorage Digital Bank N.A., the first federally chartered crypto bank in the U.S., Anchorage Digital also serves institutions through Anchorage Digital Singapore, Porto by Anchorage Digital, and other offerings. The company is funded by leading institutions including Andreessen Horowitz, GIC, Goldman Sachs, KKR, and Visa, with its Series D valuation over $3 billion. Founded in 2017 in San Fran‑cisco, California, Anchorage Digital has offices in New York, New York; Porto, Portugal; Singapore; and Sioux Falls, South Dakota. Learn more at anchorage.com, on X @Anchorage, and on LinkedIn. Join Anchorage Digital’s Global Analytics team as a Data and Reporting Architect and shape the technical foundation that powers mission‑critical reporting across the organization. You’ll design data architectures and reporting systems that ensure accuracy, reliability, and auditability for high‑stakes use cases including stablecoin reserves, trading and settlement reconciliation, regulatory reporting, and executive decision‑making. In this role, you’ll serve as the technical lead for our most complex data challenges, establishing patterns and standards that the team will follow. You’ll work at the intersection of cutting‑edge blockchain technology and regulated finance, designing solutions for stablecoin reconciliations, staking operations, custody reporting, and financial settlements. You’ll partner with Finance, Compliance, Product, and Engineering, and executive leadership to architect data models and reporting systems that can withstand external audits and regulatory scrutiny while scaling with business growth. If you’re passionate about building reliable data systems, mentoring engineers, and solving hard technical problems in a high‑impact domain, this role is for you.

Technical Skills

• Design data architectures and modeling patterns that span multiple business domains; establish conventions for dimension modeling, fact table design, slowly changing dimensions, and temporal data handling
• Architect semantic layers and BI infrastructure with focus on governance, discoverability, and self‑service; design LookML patterns and Explore structures that balance flexibility with guardrails
• Define and implement data quality frameworks including automated testing strategies (dbt tests, reconciliation checks, anomaly detection), observability patterns, and SLA monitoring
• Make principled architectural decisions on technology choices, materialization strategies, and optimization approaches (partitioning, clustering, incremental models, caching); balance performance, cost, and maintainability trade‑offs
• Establish code standards, review practices, and technical documentation patterns for the analytics team; mentor analysts on advanced SQL techniques, data modeling principles, and software engineering best practices

Complexity and Impact of Work

• Own the technical architecture for multiple domain areas end‑to‑end; ensure reporting meets audit, regulatory, and executive requirements
• Design and implement reporting systems that support external audits and regulatory examinations; establish audit trails, data lineage, and control frameworks that demonstrate effective oversight
• Lead resolution of complex data quality incidents and reconciliation breaks; perform root cause analysis across multiple systems, design permanent fixes, and implement preventive controls
• Drive strategic technical initiatives such as data platform migrations, BI tool consolidation, or implementation of new data governance frameworks; coordinate work across analytics, engineering, and business teams
• Anticipate future business needs and design data architectures that can evolve; balance solving immediate problems with building reusable, scalable infrastructure
• Establish metrics and monitoring for data quality, pipeline reliability, and reporting SLAs; drive continuous improvement in operational excellence

Organizational Knowledge

• Develop expert‑level understanding of Anchorage Digital’s business model, regulatory environment, and technical architecture; understand data flows across custody, staking, stablecoins, trading, and banking operations
• Build trusted advisor relationships with senior stakeholders in Finance, Trading, Risk, and executive leadership; become the go‑to technical expert for data architecture and reporting questions
• Partner with Data Platform engineers on infrastructure strategy; influence roadmap and design decisions for shared data services, tools, and platforms
• Mentor and develop analytics engineers on the team; provide technical guidance, conduct design reviews, and help team members grow their technical skills
• Document architectural decisions, design patterns, and domain knowledge; establish knowledge‑sharing practices that scale as the team grows
• Represent the analytics team in cross‑functional technical discussions; advocate for data quality, observability, and analytics engineering best practices

Communication and Influence

• Present complex technical architectures and design decisions to senior leadership and executive audiences; distill technical details into business impact and risk trade‑offs
• Lead design reviews and architectural discussions; facilitate consensus on contentious technical decisions; document rationale for future reference
• Work with external auditors and regulators to explain data architectures, reconciliation logic, and control frameworks; respond to technical questions with precision and transparency
• Write clear, comprehensive technical documentation including architecture decision records, data model specifications, and operational runbooks
• Influence technical culture and standards across the analytics organization; champion best practices for code quality, testing, and documentation
• Navigate difficult stakeholder conversations when requirements conflict with technical feasibility or best practices; propose alternative solutions and manage expectations effectively

Fit for this role

• 6+ years of experience in analytics engineering, data engineering, or related roles with increasing responsibility for data architecture and technical leadership
• Expert‑level data modeling skills with proven ability to design dimensional models, establish modeling patterns, and make principled trade‑offs across multiple business domains
• Deep expertise in SQL and data transformation including advanced optimization, performance tuning, and writing maintainable, production‑quality code at scale
• Extensive experience with modern BI platforms (Looker strongly preferred) including semantic layer design, governance patterns, and building self‑serve analytics at scale
• Proven experience with dbt or similar transformation frameworks including establishing project structure, testing strategies, documentation patterns, and CI/CD workflows
• Strong foundation in data quality and testing with experience implementing automated validation, reconciliation frameworks, and observability patterns
• Experience with Python‑based data tools including pandas, data validation libraries, or API development for data services
• Experience with orchestration platforms (Airflow, Dagster, Prefect, or Argo) and designing reliable, observable data pipelines
• Cloud data warehouse expertise (BigQuery, Snowflake, or Redshift) with deep understanding of optimization techniques, cost management, and performance tuning
• Technical leadership experience including mentoring engineers, conducting design reviews, establishing coding standards, and driving adoption of best practices
• Excellent communication skills with proven ability to present technical content to executive stakeholders and translate between business requirements and technical architecture
• Track record of delivering high‑quality results in fast‑paced, high‑stakes environments with incomplete information and competing priorities

Bonus points

• Experience in financial services, fintech, or cryptocurrency/blockchain companies
• Knowledge of blockchain data and on‑chain analytics
• Data platform or infrastructure engineering experience
• Background in financial reporting, accounting, or audit with understanding of GAAP principles, financial statement preparation, or reserve methodologies

About Anchorage Digital

About Anchorage Digital: Who we are The Anchorage Village, what we call our team, brings together the brightest minds from platform security, financial services, and distributed ledger technology to provide the building blocks that empower institutions to safely participate in the evolving digital asset ecosystem. As a diverse team of more than 600 members, we are united in one common goal: building the future of finance by providing the foundation upon which value moves safely in the new global economy. Anchorage Digital is committed to being a welcoming and inclusive workplace for everyone, and we are intentional about making sure people feel respected, supported, and connected at work—regardless of who you are or where you come from. We value and celebrate our differences and we believe being open about who we are allows us to do the best work of our lives.

Anchorage Digital is an Equal Opportunity Employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. Anchorage Digital considers qualified applicants regardless of criminal histories, consistent with other legal requirements.

Protecting your privacy rights is important to Anchorage Digital, and we work to maintain the trust and confidence of our clients when handling personal or financial information. Please see our privacy policy notices here. 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.