Go-to-Market Engineer, Data Operations

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Maleda Tech

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

📦 Logistics

🎯 Recruiter

Consulting • Logistics • Recruitment

Maleda Tech is a global contingent workforce solutions provider offering Employer of Record (EOR) services, Managed Service Provider (MSP) programs, Vendor Management System (VMS) implementation, staff augmentation, recruiting, strategic sourcing, tail spend management, and legal/contract operations. They position themselves as a personalized, boutique partner focused on risk compliance and efficient hiring, with an emphasis on diversity (committed to recruiting at least 85% of employees from diverse backgrounds). The company also runs immersive training and mentorship programs to build candidate pipelines and has operations in the Bay Area (California, US) and Addis Ababa (Ethiopia).

📋 Description

• Manage the data sources the team accesses, spanning internal company data and publicly available third-party data. • Clean, combine, and present structured and unstructured data into unified, actionable views that supply teams and account managers can actually use. • Build on top of Clay platform outputs and integrate them with internal data warehouse sources and other third-party data. • Support lead enrichment across supply verticals such as hotels, homes, services, and experiences, partnering with vertical stakeholders to source, clean, and consolidate data into a single usable view. • Translate business requirements from revenue operations, sales, and growth into working systems and prototypes rather than recommendations alone. • Contribute to internal tooling and prototype development that puts enriched data to work across go-to-market motions, including lead sourcing, outreach sequencing, and CRM hygiene. • Evaluate third-party data vendors and enrichment tools, identify gaps in current data coverage, and help close them.

🎯 Requirements

• Clay platform experience, which is non-negotiable, as it is the team's current platform of choice. • Roughly one year or more is a helpful benchmark, though proof of what you have built matters most • SQL proficiency, enough to query internal data sources, investigate and validate data, and build integrations with the data warehouse and other third-party sources • A strong instinct for data quality, with the ability to navigate complex, fragmented data structures, connect business use cases back to the underlying data, and judge whether that data can be trusted • The ability to combine structured and unstructured data and present it clearly to non-technical business stakeholders • A flexible background, as startup, consulting, and enterprise experience are all valid, and what you have done matters more than where you did it. • Data storytelling, dashboarding, or BI capabilities, though a dedicated analytics background is not required. • Workflow automation experience with n8n or Zapier, which is a plus rather than a dealbreaker. • Python or TypeScript for lightweight data transformations or API integrations. • Experience leveraging multiple third-party data sources such as ZoomInfo, LinkedIn, and Clay. • A marketplace or platform-company background where data coverage directly drives top-of-funnel outcomes. • Experience with AI and automation tools such as Retool and n8n for building lightweight internal tools.