Data Architect – Mid-Level

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 16%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Irth Solutions

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 1995

☁️ SaaS

⚡ Energy

📡 Telecommunications

💰 Private Equity Round on 2015-07

SaaS • Energy • Telecommunications

Irth Solutions is a market-leading provider of a SaaS platform focused on enhancing resilience and reducing risk in the management of critical network infrastructure. Their solutions are trusted by energy, utility, and telecom companies across the U. S. and Canada, offering capabilities in damage prevention, training, asset inspections, land management, and 811 ticket management. By leveraging business intelligence, analytics, and geospatial data, Irth Solutions provides comprehensive situational awareness to proactively manage and mitigate risks in network infrastructure. The acquisition of OneBridge Solutions enhances their asset performance management offerings.

📋 Description

• Design the schema and unified data model for the platform, spanning asset, inspection, incident, geospatial, and consequence data across multiple products • Apply Bronze, Silver, and Gold medallion architecture patterns and define the semantic layer consumed by downstream models, reporting, and applications • Model data required by probabilistic risk models, defining sources, transformation paths, and data-quality expectations for required input attributes • Design cross-product entity resolution for shared assets and entities • Define ingestion patterns for batch, streaming, and CDC sources, including schema evolution and slowly changing dimensions • Produce architecture documentation, diagrams, data dictionaries, and decision records • Design the shared GIS layer, including pipeline centerlines, consequence-area polygons, right-of-way corridors, and parcel data • Model linear referencing and dynamic segmentation for aligning risk results with centerline geometry • Define data structures for inspection data, repair history, weather history, soil characteristics, and satellite-derived data • Define cataloging, classification, metadata, and lineage standards in Unity Catalog • Establish data-quality rules, validation gates, profiling, quarantine, and remediation processes • Define access-control patterns, tenant isolation, and sensitive-data handling • Design end-to-end traceability from risk outputs to source records • Work with data engineers to implement architectural designs and review production pipelines • Contribute to schema deployment, transformation logic, and optimization • Partner with application engineers and data scientists on serving layers, feature stores, and APIs • Support performance and cost optimization through partitioning, clustering, file layout, and compute sizing • Participate in design reviews and architecture alignment sessions • Translate domain and regulatory requirements into data structures and standards • Maintain current architecture documentation • Deliver a documented and implemented data model supporting risk-model inputs, strong lineage, traceability, implementation clarity, and reliable entity resolution

🎯 Requirements

• 5–8 years of experience in data architecture, data modeling, or senior data engineering, including end-to-end ownership of a non-trivial data model • Hands-on experience with Databricks, including Delta Lake, Unity Catalog, SQL Warehouses, and pipeline orchestration • Strong command of medallion and lakehouse architecture patterns, dimensional modeling, and semantic layer design • Advanced SQL skills and proficiency in Python or PySpark • Experience with at least one major cloud platform; Azure experience preferred • Practical experience with change data capture (CDC), slowly changing dimensions (SCD), schema evolution, and data-quality frameworks • Working knowledge of data governance, including cataloging, lineage, classification, role-based access control (RBAC), and encryption • Strong documentation and diagramming skills, with the ability to explain data models clearly to both technical and non-technical stakeholders • Experience designing geospatial data models and working with GIS tooling, spatial joins, and linear referencing • Experience with multi-tenant platforms, data residency requirements, or regulated environments • Familiarity with metadata and lineage tools such as Unity Catalog, Microsoft Purview, or equivalent platforms • Experience modeling data specifically for machine learning or probabilistic risk models • Experience designing semantic layers for business intelligence (BI) consumption • Databricks or cloud data certifications • Experience using AI-assisted coding tools such as Cursor or GitHub Copilot and/or agentic coding tools such as Claude Code as part of a professional development workflow • Familiarity with pipeline or utility asset data, including inline inspection results, alignment sheets, facilities, and centerline geometry • Understanding of asset integrity concepts such as corrosion growth, defect tracking, and consequence-of-failure modeling • Awareness of regulatory reporting requirements applicable to pipeline integrity data • Experience migrating data from legacy desktop or spreadsheet-based systems