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Lead Architect - Analytics Engineering Jobs (Hybrid work)

366 Job Offers

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Software Engineering Manager
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Hungary , Budapest
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Formlabs GmbH
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React Architect
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Turkey , Istanbul
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Amaris Consulting
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Principal Architect, Systems (Oracle Commerce Cloud & ERP Transformation Architect)
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United States , Bellevue; Atlanta; Frisco
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123800.00 - 223300.00 USD / Year
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T-Mobile
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Senior Infrastructure Engineer
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Finland , Helsinki
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ICEYE
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Staff Electronics Engineer
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Finland , Espoo
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ICEYE
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Senior Java Engineer
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Philippines , Makati City
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Avaloq
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Software Engineer II (Frontend)
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United Kingdom , Belfast
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41000.00 - 54000.00 GBP / Year
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Fin Capital
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Multi Cloud Architect
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India , Bangalore South
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Wissen
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Senior Maximo Consultant
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United Kingdom , London
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Bentley Systems
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Manager, Product Engineering
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United States , New York City
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153000.00 - 270300.00 USD / Year
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Braze
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Senior Software Engineer In Test
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United Kingdom , London
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Axon
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Firewall Administrator
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United States , Philadelphia
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Ocean Blue Solutions
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Confirmed Software Engineer - Workflow & Operations
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France , Paris
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55000.00 - 60000.00 EUR / Year
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Implicity
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Senior Backend Engineer
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Singapore , Singapore
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Ethos
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Senior AI Security Engineer
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United Kingdom , London
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Citi
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Java Full Stack Developer
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United States , Irving; Tampa
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125760.00 - 188640.00 USD / Year
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Citi
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Digital Presales Solutions Architect
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Costa Rica , Heredia
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Hewlett Packard Enterprise
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Infosec Senior Analyst
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Hungary , Budapest
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Citi
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Application Architect - Risk Technology
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United Kingdom , London
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Citi
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Cyber Engineering Senior Analyst
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Hungary , Budapest
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Citi
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Embark on a rewarding career path by exploring Lead Architect - Analytics Engineering jobs, a pivotal senior role at the intersection of data strategy, business intelligence, and software engineering. A Lead Architect in Analytics Engineering is the visionary and technical mastermind responsible for designing, building, and scaling an organization's data analytics infrastructure. This profession is not just about managing data; it's about architecting the very foundation that transforms raw, disparate data into a reliable, accessible, and actionable asset for the entire company. Professionals in these jobs act as the bridge between data engineers, who build data pipelines, and data analysts or business intelligence teams, who consume the data for insights. Their core mission is to create a robust, scalable, and efficient data platform that empowers self-service analytics and drives data-informed decision-making across all departments. Common responsibilities include designing the overall data architecture and modeling strategy, establishing best practices for data governance, quality, and documentation, and selecting the appropriate technology stack (including data warehouses, transformation tools, and BI platforms). They lead the development of clean, tested, and well-documented data models—often using frameworks like dbt (data build tool)—to create a single source of truth for key business metrics. Furthermore, they mentor and guide a team of analytics engineers, fostering a culture of technical excellence and collaboration. Typical skills and requirements for Lead Architect - Analytics Engineering jobs are extensive. A strong foundation in advanced SQL is non-negotiable, coupled with deep expertise in data modeling concepts (e.g., dimensional modeling, Data Vault). Proficiency with modern data stack technologies like Snowflake, BigQuery, Redshift, dbt, Airflow, and Git is essential. Beyond technical prowess, successful candidates possess exceptional leadership and communication skills to articulate complex technical concepts to non-technical stakeholders and align data initiatives with overarching business goals. They are strategic thinkers, adept at performance tuning, and have a proven track record of managing large-scale data projects from conception to deployment. If you are a data professional passionate about building elegant, scalable data systems and leading high-performing teams, searching for Lead Architect - Analytics Engineering jobs will open doors to a critical and high-impact career where you shape the data-driven future of modern enterprises.

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