About The Position

This is a senior level technical architect role responsible for defining the target architecture and leading the design and build of an end-to-end enterprise data platform, including a lakehouse on Databricks or AWS native services and a governed data warehouse on Snowflake. Operating with broad autonomy and enterprise level influence, this role sets platform standards and makes high impact technical decisions across ingestion, lakehouse storage/compute, Snowflake warehousing, transformation, governance, and consumption. Architectural standards and patterns defined by this role serve as the technical foundation that engineering delivery teams build against, ensuring consistency and alignment across the platform. The architect partners closely with functional executives, cross-functional leaders, and select external vendors, while remaining hands-on through architecture reviews, POCs, and critical path build activities. This position is accountable for solving ambiguous, complex, and high risk platform problems in a greenfield environment where choices around lakehouse patterns, Snowflake modeling, data movement, and governance establish long-term direction and impact multiple processes, functions, and enterprise outcomes.

Requirements

  • 10+ years designing and building enterprise scale data platforms, including lakehouse and data warehouse architectures
  • Deep hands-on experience with Databricks and/or AWS native lakehouse services, and strong working knowledge of Snowflake (architecture, modeling, performance, and security).
  • Strong command of BI ready data modeling (dimensional and/or data vault), semantic layer design/management, and enabling BI tools on top of Snowflake and/or curated lakehouse gold layers.
  • Experience implementing data quality frameworks (rules, monitoring, SLAs) and partnering on master data management (MDM) to deliver trusted, consistent dimensions across domains.
  • Proven track record influencing senior leaders without formal authority
  • Comfortable operating in ambiguity, making decisions that last, and balancing scalability, governance, performance, and cost across the platform.
  • Active, habitual use of AI development tools (e.g., GitHub Copilot, Claude Code, Cursor, or similar) to accelerate personal delivery of POCs, reference implementations, and architectural artifacts.

Responsibilities

  • Architect and lead delivery of an end-to-end enterprise data platform with a lakehouse (Databricks or AWS native) and a Snowflake data warehouse, including ingestion, transformation, serving, and consumption through BI tools and a governed semantic layer.
  • Design lakehouse patterns (e.g., bronze/silver/gold, Delta/Apache Iceberg where applicable), including data quality controls and master data management (MDM) integration, and define the approach into Snowflake (ELT, CDC, data sharing, and performance-optimized loading).
  • Ensure data products are scalable, trusted, secure, and performant by defining SLAs/SLOs, data quality controls, lineage, and operational monitoring across the lakehouse and warehouse.
  • Influence functional executives and cross‑functional leaders by being the strongest technical voice in the room.
  • Build and validate solutions hands-on through POCs, reference implementations, architecture reviews, and direct contribution to Databricks/AWS pipeline patterns and Snowflake models.
  • Define platform guardrails for security and governance (e.g., encryption, IAM integration, RBAC, PII handling, auditability) across the lakehouse and warehouse.
  • Identify and introduce architectural standards, patterns, and tools that measurably improve platform speed, reliability, cost efficiency, or security — translating architectural decisions into tangible operational and financial outcomes.
  • Drive outcomes that affect enterprise operations, financials, and executive reporting trust.
  • Define platform processes, patterns, and standards for data ingestion/CDC, transformation (ELT), orchestration, CI/CD, testing, and release management.
  • Establish architecture standards and guardrails for Databricks/AWS lakehouse and Snowflake warehouse patterns, including workload separation, cost management, and performance tuning.
  • Operate effectively in ambiguous, fast-moving conditions — challenge established patterns, evaluate emerging tools and approaches (including AI-native capabilities), and adapt platform direction as the technology landscape shifts.
  • Design for AI-native platform capabilities where they improve operational efficiency, including intelligent monitoring, automated anomaly detection, data quality remediation, and stewardship automation — while keeping the core focus on building a reliable, well-governed data platform. Ensure the semantic layer, catalog, and metadata architecture are designed to support AI-enabled analytics capabilities
  • Lead major platform initiatives and influence work across teams based on expertise.
  • Provide input into technical hiring and capability development.

Benefits

  • Inclusive health, dental, vision and life insurance plans built to support diverse lifestyles, offer preventative care, and protect against hardship.
  • Easy access to mental health benefits to meet our team members and their families where they are.
  • 20 plus days of paid time off (PTO), paid holidays, and 2 paid wellness days to give our employees the time they need to stay close with their loved ones, recharge, and give back to their communities.
  • 401(k) Savings plan with a generous company contribution (up to 5%), and access to a financial professional to offer our employees the opportunity to plan-ahead for a strong financial future well beyond their working years.
  • Paid parental leave to support all team members with birth, adoption, and foster.
  • Health Savings and Flexible Spending Account options to help you save money on healthcare, daycare, commuting, and more.
  • Employee Assistance Program (EAP), LifeLock, Pet Insurance and more.
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