Principle Data Architect Snowflake Lakehouse- Remote

What You Will Own

Account Topology and Convergence
Define the target account topology: a small set of core accounts plus governed spokes for customer-facing, embedded or regulated workloads.
Apply a decision framework to every existing account: retire it if it has no owner or activity, merge enterprise analytics into the core enterprise account, converge product and telemetry data into the Construction Data Cloud, and keep an account as a spoke only when a product feature, region, edition or regulation requires it.
Design environments as databases inside non-production accounts, with separate warehouses and roles so each team keeps its own compute, access and cost view.
Sequence the migrations with each account owner and approve every new account and exception through the Architecture Review Board.

Medallion and Lakehouse Standards
Publish the Bronze, Silver and Gold definitions, database and schema standards, naming conventions and data contract patterns, with a reference implementation that teams can copy.
Architect the decoupled raw layer on Iceberg tables in S3 and define how it relates to Snowflake-managed tables, including change data capture.
Produce one reference architecture diagram that becomes the enterprise standard and is understood by both executives and engineers.

Access and Security Architecture
Design role-based and attribute-based access control, tagging, classification, masking and row access policies, and secure sharing with external parties.
Align the design with the governance framework (sector, data domain and job function) and with enterprise identity governance, so that access decisions are auditable and meet SOX requirements.

Cost, Performance and Capacity
Set warehouse design standards, resource monitors and performance practices.
Attribute platform spend to a domain for every account and workload, and support chargeback and forecasting.
Report cost and capacity against targets to the Head of Data and the platform leadership monthly.

Enablement of Domain Teams
Provide templates and reference implementations for dbt projects, semantic views, pipelines and data contracts, so domain pods start from a working pattern.
Run the architecture review with a defined turnaround time. Approve by default when a team follows the standard, and spend review time on real exceptions.
Coach analytics engineers in the domain pods on design and performance.

AI-Ready Architecture
Govern the enterprise semantic layer as the controlled source of business definitions for analysts, Cortex features and agents.
Ensure agents and AI features read certified Gold data only, and define the API, GraphQL and MCP patterns through which data leaves the platform.
Design for product telemetry at scale in support of the Construction Data Cloud.

Platform Decisions
Evaluate and recommend platform components, such as the catalog, observability and orchestration tools, with the Head of Data, and document each decision with its trade-offs.

Your First 90 Days
Complete the inventory of Snowflake accounts, owners, spend and lineage, and classify each account with the decision framework.
Publish the target topology and the migration sequence for the first wave of accounts.
Publish version one of the medallion and naming standard with a reference implementation.
Agree the data contract template at the Bronze boundary with the Enterprise Data Architect for Business Systems and Transformation.
Set a turnaround time for architecture reviews and publish it to the domain teams.

How This Role Works With the Enterprise Data Architect
This role owns everything from the Bronze layer onward: platform topology, medallion standards, access, cost and serving. The Principal Enterprise Data Architect, Business Systems and Transformation owns how Fusion, Salesforce and Reltio structure and reconcile data up to the contract at Bronze. The two share ownership of that contract and take unresolved disputes to the Head of Data.

Qualifications

Required Experience
12+ years in data architecture, data engineering or data platform roles, with at least 5 years architecting Snowflake at enterprise scale, including multi-account and organization-level design, replication and data sharing.
Proven design of medallion or lakehouse architectures at scale, including open table formats such as Iceberg on cloud object storage.
Expert SQL, and working fluency in dbt and modern ELT practices.
Design experience with role-based and attribute-based access control, tagging, masking and row access policies on Snowflake.
Experience governing platform cost, including attribution of spend to teams and chargeback.
Experience consolidating or reorganizing a sprawling data estate while teams continue to deliver.
A record of enabling federated teams to build within standards rather than centralizing their work.
Strong working knowledge of AWS data services.

Strong Signal Qualifiers
SnowPro Advanced: Architect certification.
Experience with Snowflake semantic views, Cortex and agent-facing data access patterns.
Experience with Fivetran, Atlan, Monte Carlo and infrastructure as code for Snowflake.
Experience operating in a federated or data-as-a-product model with domain-aligned teams.
Experience with product telemetry or IoT data at scale, ideally in construction, engineering or industrial technology.
Grounding in DAMA-DMBOK or DCAM