Data Scientist / Analytics Engineer

Clarity Cubed is an early-stage data and analytics company helping middle-market businesses build data ecosystems by connecting data across systems, cleaning data, and positioning data to support the business and drive value creation. We work hands‑on with real operating systems (ERP, CRM, finance, ops), turning messy, fragmented data into a reliable ecosystem that is core to how a business is run. We are not an academic lab or a dashboard factory. We build practical data systems that work in the real world. We marry business acumen and experience with technical expertise to design thoughtful solutions that unlock value. This data hire will help us deliver client work and shape how we build going forward. The Role This is a hands‑on hybrid role spanning data engineering, analytics, and system design. You will design and build SQL‑ and Python‑based workflows that ingest, clean, transform, and connect data across systems. You will own pipelines end‑to‑end and help drive analytics on top of them. You will also help build the IP that monitors these ecosystems and drives AI based workflows on top of the structured data sets. You will also have client exposure and the opportunity to shape Clarity Cubed’s internal IP, standards, and approach from the ground up. What You’ll Do Design, build, and maintain SQL‑ and Python‑based data workflows Develop robust ETL/ELT pipelines and orchestration processes Work extensively with messy, real‑world operational and financial data Model data in Snowflake and similar cloud data warehouses Build secure, reliable connectivity across systems, using APIs exports and manual loads Partner with clients to understand business context and translate it into data solutions Support analytics use cases on top of engineered data sets Contribute to and help shape Clarity Cubed’s internal tools, templates, and best practices Explore and experiment with emerging AI tools as part of the data workflow (interest required; deep ML not required) What We’re Looking For 4–10 years experience in data science, analytics engineering, or data engineering Strong, hands‑on experience with SQL (advanced queries, modeling, performance) Strong experience with Python for data processing and pipeline development Experience building and orchestrating production data pipelines Familiarity with Snowflake or similar cloud data platforms (preferred) Comfort working across APIs and systems securely Ability to operate independently and own problems end‑to‑end Comfort with ambiguity and early‑stage environments Clear, direct communicator who can work with both technical and non‑technical stakeholders Entrepreneurial mindset and interest in building something from the ground floor Nice to have Experience with Power BI or other BI tools Exposure to financial or operational data Consulting or client‑facing experience Interest in applied AI tools and workflows How We Work In‑person team based in Dumbo, Brooklyn Early‑stage, high‑ownership environment Reasonable hours with real responsibility and trust Minimal travel (unless of interest) Direct, plain‑spoken culture with deep practical experience Why This Role Is Different Work with founders who bring extensive hands‑on business and investing experience Help shape how data is used to drive business at medium sized enterprises You will help use data to bring clarity to business at Clarity Cubed. #J-18808-Ljbffr