Databricks Solution Architect

🕒 il y a 1 mois

⛰️ Colorado – Distant

⛰️ Colorado – Remote

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

💻 Ingénieur Solutions

👻 Score fantôme 10%

Ce que ça veut dire : la probabilité que cette offre reste ouverte sans recrutement actif.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Bits In Glass

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 2002

💼 Conseil

📦 Logistique

🏭 Fabrication

💰 Private equity en 2024-03

Consulting • Logistics • Manufacturing

Bits In Glass est une société de conseil internationale spécialisée qui conçoit, construit et gère des solutions d'automatisation intelligente et d'intégration pour des clients d'entreprise. L'entreprise se spécialise dans l'IA d'entreprise et l'ingénierie des données, le développement low-code/no-code, l'automatisation des processus (y compris RPA et BPA), l'intégration des applications d'entreprise, les implémentations CRM et les services de gestion d'applications, en collaborant avec des partenaires tels qu'Appian, AWS, UiPath, MuleSoft, Snowflake et Creatio. Bits In Glass dessert des secteurs tels que la banque et les services financiers, l'assurance, le transport et la logistique, la fabrication et la distribution, l'immobilier, la santé et le secteur public, aidant les organisations à étendre l'automatisation, à améliorer l'efficacité et à transformer les données en informations exploitables.

Description

• Design scalable Databricks solution architectures using Lakehouse, Delta Lake, and Unity Catalog patterns tailored to customer environments and business goals • Lead technical discovery workshops covering customer objectives, data challenges, and current-state architecture • Build working prototypes, proofs-of-concept, and reference architectures for the Databricks Lakehouse Platform • Guide customers on data pipeline, data modeling, and platform governance best practices • Advise on integrating Databricks with AWS, Azure, GCP, and adjacent data tooling • Demonstrate Databricks capabilities across Data Engineering, Data Science, ML, and Generative AI use cases • Identify and mitigate technical risks to prepare delivery teams for success • Translate complex technical concepts into clear business value for technical stakeholders and executives • Partner with account teams throughout the sales process to shape technical strategies • Collaborate with Data Scientists and ML Engineers on AI-powered demo assets and reference architectures • Serve as a resident Databricks expert within BIG and enable the broader team • Contribute reusable accelerators, demo assets, and technical playbooks • Stay current on Databricks releases and evolving data and AI patterns • Represent BIG at customer events, webinars, and Databricks partner activities • Provide field feedback to Databricks product and partner teams • Travel up to 15% for customer meetings and partner collaboration

🎯 Exigences

• 3+ years of hands-on experience with Databricks and/or Snowflake in a technical capacity • 5+ years in customer-facing technical roles such as solutions architecture, technical consulting, or sales engineering • Experience designing, presenting, and delivering production data architectures for enterprise customers, including Lakehouse, Delta Lake, and Unity Catalog patterns, on AWS, Azure, and/or GCP • Databricks Professional-level certification, such as Data Engineer Professional or Machine Learning Professional • Strong expertise in at least one core data domain: big data engineering, Data Warehousing & ETL, or Data Science & ML • Fluency in Python and SQL • Exceptional verbal, written communication, and presentation skills • Ability to lead business-level meetings with technical and non-technical clients and internal team members • Ability to translate complex topics into clear business value and earn buy-in from engineers and executives • Experience with Spark and Kafka, or Data Warehousing & ETL, or Data Science & ML • Nice to have: degree in Computer Science, Applied Mathematics, Operations Research, or a related quantitative field • Nice to have: experience with dbt, Fivetran, Airflow, or Delta Sharing • Nice to have: familiarity with AI/GenAI frameworks and LLM application patterns • Nice to have: Databricks GenAI Engineer Associate certification • Nice to have: exposure to enterprise engagement cycles • Nice to have: experience with frontier LLMs such as Claude Code for SDLC acceleration

🏖️ Avantages

• Join a Certified Great Place to Work with a people-first, collaborative culture • Access to 10+ cutting-edge technology practices and continuous learning opportunities • Competitive compensation • Benefits • Flexible, remote-friendly work environment • Team that celebrates wins together