Data Architect – Mid-Level

🕒 Setembro 10

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🚰 Engenheiro de Dados

👻 Score fantasma 20%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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Irth Solutions

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 1995

☁️ SaaS

⚡ Energia

📡 Telecomunicações

💰 Private Equity Round em 2015-07

SaaS • Energy • Telecommunications

A Irth Solutions é uma fornecedora líder de mercado de uma plataforma SaaS focada em melhorar a resiliência e reduzir o risco na gestão de infraestrutura crítica de rede. Suas soluções são confiáveis para empresas de energia, serviços públicos e telecomunicações nos EUA e Canadá, oferecendo capacidades em prevenção de danos, treinamento, inspeções de ativos, gestão de terras e gerenciamento de tickets 811. Ao alavancar inteligência de negócios, análises e dados geoespaciais, a Irth Solutions fornece uma consciência situacional abrangente para gerenciar e mitigar riscos proativamente na infraestrutura de rede. A aquisição da OneBridge Solutions aprimora suas ofertas de gestão de desempenho de ativos.

Descrição

• 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

🎯 Requisitos

• 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