Data & Reporting Architect

Team: Global Analytics

Location: United States

Commitment: Full-Time - Remote

Workplace Type: remote

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

You may be a fit for this role if you have:

• 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

Although not a requirement, bonus points if:

• 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
• You were emotionally moved by the soundtrack to Hamilton, which chronicles the founding of a new financial system. :)