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Meridianlink Jobs in Colorado (NOW HIRING)

Own the conceptual, logical, and physical data models for MeridianLink's analytical and operational data platform, including source-aligned, integrated, and consumption-ready layers. * Build the meta ...

Sr. Technical Project Manager (TPM)

CO · On-site +1

$110K - $152K/yr

Serve as the PMO lead for the ML's agentic platform and customer facing products - the structured methodology for developing, testing, deploying, and operating AI agents within MeridianLink's agentic ...

Experience with MeridianLink, Origence, Symitar, or similar lending platforms * Proficiency with Microsoft Office Why You'll Love Working at On Tap At On Tap Credit Union, we believe our people make ...

Meridianlink information

What is the difference between Meridianlink vs Loan Processor?

AspectMeridianlinkLoan Processor
Primary RoleSoftware platform provider for financial institutionsManages loan applications and approval processes
Work EnvironmentOffice-based, tech-focusedBanking or lending office, client-facing
Required CredentialsIT, software, or financial services backgroundFinancial or banking experience, sometimes certifications
Industry UsageFinancial technology and software industryBanking, credit unions, lending institutions

Meridianlink is a software provider specializing in financial technology solutions, while a Loan Processor is a professional managing loan applications within financial institutions. They serve different roles: Meridianlink develops platforms used by lenders, whereas Loan Processors work directly with loan files. Understanding this distinction helps clarify career paths and employer expectations in the financial services industry.

What are popular job titles related to Meridianlink jobs in Colorado? For Meridianlink jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Meridianlink jobs? Cities in Colorado with the most Meridianlink job openings:
Infographic showing various Meridianlink job openings in Colorado as of July 2026, with employment types broken down into 100% Full Time. Highlights an 47% Physical, 5% Hybrid, and 48% Remote job distribution.

Principal Data Architect

Qode

CO • On-site, Remote

Full-time

Posted 20 days ago


Job description

Principal Data Architect
About the Role:
Reporting to the Vice President of Data, the Principal Data Architect is the senior technical authority for how data is modeled, integrated, governed, and consumed across MeridianLink. You will design our enterprise data architecture end-to-end - from source-system ingestion through our Azure Databricks lakehouse and into the analytical, operational, and customer-facing data products our business depends on.
This is a hands-on role. You will not only define the meta-models, conceptual models, logical models, and physical schemas that govern our data - you will build them, prove them out in code, partner closely with data engineers as they implement them, and evolve them as the business grows. The right candidate has done this before in a FinTech SaaS environment and understands the trade-offs that come with multi-tenant data, regulated workloads, and customer-facing analytics.
What You Will Do:
  • Define the enterprise data architecture: Own the conceptual, logical, and physical data models for MeridianLink's analytical and operational data platform, including source-aligned, integrated, and consumption-ready layers.
  • Build the meta-model: Design and maintain a meta-model that captures entities, relationships, business definitions, ownership, lineage, sensitivity classifications, and SLAs - and make sure it is wired into our tooling, not stuck in a slide deck.
  • Drive the lakehouse strategy: Architect our medallion (bronze / silver / gold) Delta Lake patterns on Databricks; define standards for partitioning, clustering, schema evolution, slowly changing dimensions, and historical reproducibility.
  • Be hands-on: Write PySpark, SQL, and Delta Lake code. Build reference implementations, prototype patterns, review pull requests, and personally model critical domains rather than delegating every detail.
  • Lead data integration design: Set patterns for ingestion through Informatica Data Management Cloud (IDMC) and direct Databricks pipelines, including CDC, batch, streaming, and API-based sourcing from our SaaS products and third-party systems.
  • Champion data governance and lineage: Partner with data governance, security, and compliance leaders to operationalize cataloging, lineage, classification, masking, and access controls across the platform (Unity Catalog, IDMC, and adjacent tools).
  • Standardize data modeling practices: Establish the standards, naming conventions, and review processes used by the Data Engineering team. Coach engineers on dimensional modeling, Data Vault, and other techniques where they best fit the use case.
  • Partner across the business: Work closely with Product, Engineering, Analytics, ML, Finance, Risk, and Customer-facing teams to translate business needs into durable data designs.
  • Influence the roadmap: Identify gaps in tooling, capability, and skill; propose investments; and drive multi-quarter initiatives that materially improve how MeridianLink uses its data.

Required Qualifications
  • 12-15+ years of progressive experience in data engineering, data warehousing, and data architecture roles, with at least the most recent several years at the architect level.
  • Demonstrated experience as a Data Architect at a SaaS company in the FinTech or financial services software space (lending, banking, payments, capital markets, insurance, or a closely related domain).
  • 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 - for ingestion, transformation, and metadata-driven pipelines.
  • Proven track record of designing and implementing detailed meta-models and end-to-end data models (conceptual, logical, and physical) that have shipped to production and stood up over time.
  • Strong command of dimensional modeling (Kimball), Data Vault 2.0, and modern lakehouse patterns, including the ability to choose the right approach for the right use case.
  • Expert SQL skills and strong proficiency in Python/PySpark; comfortable writing the code, not just the diagrams.
  • Demonstrated experience implementing data governance, lineage, and metadata management programs (e.g., Unity Catalog, IDMC Data Governance, Collibra, Atlan, or similar).
  • Working knowledge of FinTech-relevant regulatory and compliance considerations (e.g., GLBA, SOC 2, PCI, NIST, state lending regulations) and how they shape data design.
  • Excellent written and verbal communication skills; able to explain complex data concepts to engineers, executives, customers, and auditors.

Preferred Qualifications:
  • 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 the underlying data domains (applicants, applications, decisions, funding, servicing, credit data, fraud, KYC/AML).
  • Experience building feature stores or curated data products that serve both ML/AI workloads and BI consumers.
  • Familiarity with Azure data services (ADLS Gen2, Azure Data Factory, Event Hubs, Synapse, Purview) and their interplay with Databricks.
  • Experience with dbt, Great Expectations, or other modern data quality and transformation tooling layered on top of Databricks.
  • Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience.

Our Data Stack:
  • Lakehouse: Azure Databricks, Delta Lake, Unity Catalog, PySpark, SQL
  • Integration: Informatica Data Management Cloud (IDMC)
  • Cloud: Microsoft Azure (ADLS Gen2, Azure Data Factory, Event Hubs, Key Vault)
  • BI & Consumption: Modern BI tooling, embedded analytics, ML feature delivery
  • Governance: Unity Catalog, IDMC governance, lineage, and data quality controls