{"schemaVersion":"jobsearcher.job.v1","id":"a37002fec65e4eae2553baa2","url":"https://jobsearcher.com/jobs/a37002fec65e4eae2553baa2","canonicalUrl":"https://jobsearcher.com/jobs/a37002fec65e4eae2553baa2","title":"Data Architect (Mid-Level)","description":"Data Architect – Insights (AI/ML)Location: Remote (US) Department: Insights (AI/ML) Reports to: Engineering ManagerAbout the RoleIrth is building a new AI-driven threat and risk management platform for pipeline asset integrity. The platform brings together three capabilities that have historically been separate at Irth:A governed, cross-product data platform built on Databricks and AzureAn AI-powered ingestion layer that normalizes, repairs, and enriches customer data without services-heavy onboardingA reusable analytical layer that runs industry-standard, Irth-developed, and customer-built risk models against the dataWe are seeking a mid-level Data Architect to design the schema and data model that powers this platform. You will create a unified structure spanning asset integrity, damage prevention, and land and stakeholder management, capable of supporting probabilistic risk models that require dozens of precisely defined input attributes per pipeline segment.This is a hands-on design role. You will establish standards for data lineage, governance, and quality while working closely with the data engineering team to implement them. This role is ideal for someone with substantial experience in lakehouse and medallion architecture who is ready to own the data model for a platform rather than a single project.Key Responsibilities1. Data Modeling & ArchitectureDesign the schema and unified data model for the platform, spanning asset, inspection, incident, geospatial, and consequence data across multiple products.Apply medallion architecture patterns (Bronze, Silver, Gold) and define the semantic layer consumed by downstream models, reporting, and applications.Model the data required by probabilistic risk models, ensuring every required input attribute has a defined source, transformation path, and data-quality expectation.Design cross-product entity resolution so records from separate products reconcile to shared assets and entities.Define ingestion patterns for batch, streaming, and change-data-capture (CDC) sources, including schema evolution and slowly changing dimensions.Produce architecture documentation, diagrams, data dictionaries, and decision records that engineers can implement without ambiguity.2. Geospatial & Domain Data DesignDesign the shared GIS layer as a first-class component of the data model, including pipeline centerlines, consequence-area polygons, right-of-way corridors, and parcel data.Model linear referencing and dynamic segmentation so risk results align with centerline geometry and can be aggregated across differing segmentations.Define data structures for inspection data, repair history, and external enrichment sources such as weather history, soil characteristics, and satellite-derived data.3. Governance, Lineage & Data QualityDefine cataloging, classification, and metadata standards in Unity Catalog and establish expectations for lineage coverage across the data estate.Establish data-quality rules, validation gates, and profiling standards, including processes for quarantining and remediating failures.Define access-control patterns, including role-based and attribute-based access, tenant isolation, and appropriate handling of sensitive data.Design for end-to-end traceability so that any risk output can be traced through every transformation back to its source record.4. Implementation PartnershipWork directly with data engineers to translate architectural designs into production pipelines and review implementations for conformance.Contribute hands-on to schema deployment, transformation logic, and optimization when it accelerates delivery.Partner with application engineers and data scientists to determine how the data model is consumed through serving layers, feature stores, and APIs.Support performance and cost optimization, including partitioning, clustering, file layout, and compute sizing.5. Collaboration & DocumentationParticipate in design reviews and architecture alignment sessions and defend design decisions using data and evidence.Work with subject-matter experts to translate domain and regulatory requirements into concrete data structures and standards.Maintain architecture documentation as the model evolves, treating stale or inaccurate documentation as a defect.","company":"Irth Solutions","rawCompany":"irth solutions","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-10-15T12:49:26.297Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Architect (Mid-Level)","description":"Data Architect – Insights (AI/ML)Location: Remote (US) Department: Insights (AI/ML) Reports to: Engineering ManagerAbout the RoleIrth is building a new AI-driven threat and risk management platform for pipeline asset integrity. The platform brings together three capabilities that have historically been separate at Irth:A governed, cross-product data platform built on Databricks and AzureAn AI-powered ingestion layer that normalizes, repairs, and enriches customer data without services-heavy onboardingA reusable analytical layer that runs industry-standard, Irth-developed, and customer-built risk models against the dataWe are seeking a mid-level Data Architect to design the schema and data model that powers this platform. You will create a unified structure spanning asset integrity, damage prevention, and land and stakeholder management, capable of supporting probabilistic risk models that require dozens of precisely defined input attributes per pipeline segment.This is a hands-on design role. You will establish standards for data lineage, governance, and quality while working closely with the data engineering team to implement them. This role is ideal for someone with substantial experience in lakehouse and medallion architecture who is ready to own the data model for a platform rather than a single project.Key Responsibilities1. Data Modeling & ArchitectureDesign the schema and unified data model for the platform, spanning asset, inspection, incident, geospatial, and consequence data across multiple products.Apply medallion architecture patterns (Bronze, Silver, Gold) and define the semantic layer consumed by downstream models, reporting, and applications.Model the data required by probabilistic risk models, ensuring every required input attribute has a defined source, transformation path, and data-quality expectation.Design cross-product entity resolution so records from separate products reconcile to shared assets and entities.Define ingestion patterns for batch, streaming, and change-data-capture (CDC) sources, including schema evolution and slowly changing dimensions.Produce architecture documentation, diagrams, data dictionaries, and decision records that engineers can implement without ambiguity.2. Geospatial & Domain Data DesignDesign the shared GIS layer as a first-class component of the data model, including pipeline centerlines, consequence-area polygons, right-of-way corridors, and parcel data.Model linear referencing and dynamic segmentation so risk results align with centerline geometry and can be aggregated across differing segmentations.Define data structures for inspection data, repair history, and external enrichment sources such as weather history, soil characteristics, and satellite-derived data.3. Governance, Lineage & Data QualityDefine cataloging, classification, and metadata standards in Unity Catalog and establish expectations for lineage coverage across the data estate.Establish data-quality rules, validation gates, and profiling standards, including processes for quarantining and remediating failures.Define access-control patterns, including role-based and attribute-based access, tenant isolation, and appropriate handling of sensitive data.Design for end-to-end traceability so that any risk output can be traced through every transformation back to its source record.4. Implementation PartnershipWork directly with data engineers to translate architectural designs into production pipelines and review implementations for conformance.Contribute hands-on to schema deployment, transformation logic, and optimization when it accelerates delivery.Partner with application engineers and data scientists to determine how the data model is consumed through serving layers, feature stores, and APIs.Support performance and cost optimization, including partitioning, clustering, file layout, and compute sizing.5. Collaboration & DocumentationParticipate in design reviews and architecture alignment sessions and defend design decisions using data and evidence.Work with subject-matter experts to translate domain and regulatory requirements into concrete data structures and standards.Maintain architecture documentation as the model evolves, treating stale or inaccurate documentation as a defect.","datePosted":"2026-10-15T12:49:26.297Z","dateModified":"2026-10-15T12:49:26.297Z","hiringOrganization":{"@type":"Organization","name":"Irth Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"a37002fec65e4eae2553baa2"},"url":"https://jobsearcher.com/jobs/a37002fec65e4eae2553baa2"}}