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 have direct client exposure and the opportunity to shape Clarity Cubed’s internal IP, standards, and approach from the ground up.
Experience: 4+ Years of Professional Experience.
Type: Full-Time position.
Location: Brooklyn, NY (Preferred).
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Design and build SQL- and Python-based workflows for data ingestion and transformation.
Own data pipelines end-to-end to drive actionable business analytics and insights.
Build internal IP that monitors ecosystems and drives AI-based workflows on structured datasets.
Ingest, clean, transform, and connect complex data across various disparate systems.
Collaborate directly with clients to shape internal standards and engineering approaches.
This role will support live client engagements and work directly on building structured, decision-ready datasets from messy real-world systems. You will operate across multiple projects, help reconcile operational data to financials, and contribute to the development of repeatable processes and internal intellectual property. Having a core background in finance/accounting and financial statement analysis is necessary in order to succeed in this position.
You will have exposure to client leadership teams and investors, while developing the skills to take on greater value creation responsibility over time.
Experience: 5+ Years of Professional Experience in Transaction Services (Valuation, Accounting Advisory, Due Diligence, M&A, Private Equity)
Type: Full-Time position.
Location: Brooklyn, NY (Preferred).
Support client engagements focused on data cleanup, reconciliation, and analysis (both financial and operational)
Work across large datasets to structure and validate information
Reconcile operational data to financial statements and management reporting
Help build recurring reporting frameworks and data models
Identify inconsistencies, gaps, and areas for improvement in client data environments
Operate across multiple projects with urgency and strong organization
Contribute to the development of scalable workflows and internal playbooks
As you grow, you will have the opportunity to take on more ownership in client workstreams and contribute directly to value creation initiatives
