Principal Data Architect

Nextdeavor•Irvine, CA

5d•Remote

About The Position

Exclusive confidential search — details shared with qualified applicants. Become a Key Player as a Principal Data Architect. You will design and build the enterprise data architecture that enables analytics, operations, and customer-facing data products for the organization. You will partner with product, engineering, analytics, ML, finance, risk, and customer-facing teams to translate needs into durable data designs. This is a hands-on, remote role where you will both define standards and implement critical models and reference implementations.

Requirements

12–15+ years of progressive experience in data engineering, data warehousing, and data architecture, with several recent years at the architect level.
Demonstrated experience as a Data Architect at a SaaS company in FinTech or financial services software.
Deep, hands-on expertise with Databricks and PySpark on Azure, including Delta Lake, Unity Catalog, structured streaming, and performance tuning at scale.
Production experience with Informatica Data Management Cloud (IDMC) or comparable enterprise integration platforms.
Proven track record designing and shipping meta-models and end-to-end data models (conceptual, logical, physical) to production.
Strong command of dimensional modeling (Kimball), Data Vault 2.0, and modern lakehouse patterns; ability to choose the right approach per use case.
Expert SQL skills and strong proficiency in Python/PySpark; comfortable writing production code.
Experience implementing data governance, lineage, and metadata management programs.
Working knowledge of FinTech-relevant regulatory and compliance considerations (e.g., GLBA, SOC 2, PCI, NIST, state lending regulations).
Excellent written and verbal communication skills; able to explain complex data concepts to engineers, executives, customers, and auditors.

Nice To Haves

Prior experience designing data architectures for multi-tenant SaaS platforms with customer-facing analytics or embedded reporting.
Experience supporting loan origination, deposit account opening, or other consumer lending workflows and related data domains (applicants, applications, decisions, funding, servicing, credit data, fraud, KYC/AML).
Experience building feature stores or curated data products serving ML/AI workloads and BI consumers.
Familiarity with Azure data services (ADLS Gen2, Azure Data Factory, Event Hubs, Synapse, Purview) in conjunction with Databricks.
Experience with dbt, Great Expectations, or other modern data quality and transformation tooling on Databricks.
Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or related field, or equivalent experience.

Responsibilities

Define the enterprise data architecture across conceptual, logical, and physical models for analytical and operational platforms.
Design and maintain a meta-model capturing entities, relationships, business definitions, ownership, lineage, sensitivity classifications, and SLAs; integrate it with tooling.
Architect and drive lakehouse strategy (medallion bronze/silver/gold Delta Lake patterns), including partitioning, clustering, schema evolution, SCDs, and reproducibility.
Write PySpark, SQL, and Delta Lake code; build reference implementations, prototype patterns, review pull requests, and personally model critical domains.
Set patterns for ingestion via enterprise integration platforms and Databricks pipelines, including CDC, batch, streaming, and API-based sourcing.
Partner with governance, security, and compliance to operationalize cataloging, lineage, classification, masking, and access controls (e.g., Unity Catalog, IDMC).
Establish and standardize data modeling practices, naming conventions, and review processes; coach engineers on dimensional modeling and Data Vault approaches.
Identify tooling and capability gaps, propose investments, and drive multi-quarter initiatives to improve how the organization uses data.