Analytics Architect

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🕒 May 19

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InterWorks

51 - 200 employees

🏢 Enterprise

☁️ SaaS

Enterprise • AI • SaaS

InterWorks is a versatile technology consulting firm focused on delivering innovative solutions across various domains such as AI, enterprise application development, 3D solutions, and cloud infrastructure. They excel in data analytics and business intelligence, providing transformative insights for informed decision-making. InterWorks is committed to optimizing IT operations with effective support services. Their product suite includes tools for virtual storytelling, e-commerce enhancement, and AI-powered project management, which are designed to boost efficiencies and streamline operations. Furthermore, InterWorks actively engages in sustainability initiatives, aiming to make a positive impact on the world.

📋 Description

• Lead enterprise analytics engagements end-to-end — from scoping and solution design through delivery, documentation, and client enablement. • Architect and build governed metric definitions, reusable data models, and self-service analytics that scale. • Design and deliver Sigma Apps, including input tables, write-back workflows, and workbook-as-product patterns. • Design and implement AI-enabling data infrastructure: context pipelines, metadata layers, and governance frameworks that make data assets discoverable, trustworthy, and ready for AI consumption at scale. • Architect systems integrations that connect CDWs, semantic layers, BI surfaces, and operational systems into coherent, governed data products. • Serve as a trusted pre-sales partner — help scope engagements, contribute to proposals, and help prospects understand the art of the possible. • Establish and evangelize software and analytics engineering standards — metric definitions, CI/CD, data model conventions, and governance patterns — across client organizations and internally at InterWorks. • Mentor consultants on project-based engagements, providing technical guidance and supporting professional development. • Build capability areas through internal solutions, reusable assets, and external partnerships.

🎯 Requirements

• 5+ years in analytics or data engineering, with meaningful experience in an Analytics Engineering capacity - not just BI development. • Strong, production-level SQL skills and hands-on experience with dbt - modeling, testing, documentation, and ideally semantic layer integration. • Experience in Python for data transformation, pipeline logic, or analytics tooling - comfortable in code, not necessarily a software engineer. • Experience with version control (Git) and modern software development workflows applied to analytics work (CI/CD, PR reviews, automated testing). • Cloud data warehouse depth in at least one of: Snowflake, Databricks, or BigQuery. • Experience with BI platforms like Tableau and PBI. • Proven success leading complex, multi-stakeholder projects with real delivery accountability. • Strong communication skills, both technical and consultative. • Comfort with ambiguity and a track record of bringing structure to evolving, client-facing situations.

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