Technical Business Analyst - Revenue Operations

AI overview

Shape and optimize data processes, ensuring robustness in revenue tracking and seamless integration with partners while driving product evolution.

We are seeking a Technical Business Analyst to shape and optimize the processes for ingesting, validating, and tracking partner revenue data. You will play a vital role in ensuring the robustness and alignment of data pipelines and partner integrations. This hands-on, product-facing role combines data fluency with stakeholder management. You will work with internal teams to define requirements and validate new integrations, driving the evolution of our revenue data products. Direct engagement with external partners to ensure smooth onboarding, data quality, and reliability is also expected.

This position is ideal for candidates with strong analytical skills, a technical mindset, and an interest in transitioning towards product ownership.

Responsibilities:

Partner & Data Integration

  • Lead the onboarding, validation, and documentation of new partner data sources and integrations.
  • Collaborate with Data Engineering to define and test ingestion logic using APIs, file feeds, and offline uploads.
  • Maintain consistency and completeness in revenue tracking, identifying and resolving data discrepancies.

Business Analysis & Documentation

  • Translate business and partner requirements into clear, actionable technical specifications.
  • Develop QA plans for QA teams and assist with validation as needed.
  • Maintain up-to-date documentation for partner data flows, schemas, and dependencies.

Cross-Team Collaboration

  • Collaborate closely with Sales, Data Engineering, and Program Management to align priorities and ensure smooth delivery.
  • Drive conversations with the sales team to establish strong data partnerships.
  • Work with external partners to clarify data requirements, troubleshoot integration issues, and communicate changes effectively.
  • Act as a key liaison between commercial and technical teams, ensuring mutual understanding of the project goals and builds.

Continuous Improvement & Impact

  • Evolve data ingestion frameworks to support faster and more accurate onboarding of new partners.
  • Contribute to enhancing data visibility, QA coverage, and partner trust.
  • Develop a working knowledge of attribution and monetization models to link data pipelines with business outcomes effectively.

Requirements:

  • Strong technical understanding of data pipelines and revenue tracking systems.
  • Experience in the Affiliate Marketing space from either publisher, platform, or agency side.
  • Proficiency in SQL for validation or QA, and comfort in working within BigQuery (or similar environments).
  • Familiarity with API-based integrations, file feeds, or offline conversion uploads.
  • Excellent stakeholder communication skills - simplifying technical topics for commercial teams and vice versa.
  • Experience in affiliate, lead generation, or performance marketing businesses.
  • Strong organizational skills, attention to detail, and ability to manage multiple priorities.
  • Collaborative, curious, and proactive mindset.
  • Familiarity with GA4 or other marketing analytics platforms.

Nice to Have

  • Experience with Tableau or similar BI tools.
  • Familiarity with marketing data from DSPs (Google, Meta, etc.).
  • Understanding of lifetime value modelling.

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

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Forbes Advisor is looking for a Data Research Engineer - Data Extraction to join the Forbes Marketplace Performance Marketing team with a focus on supporting one of Forbes business verticals. If you're looking for challenges and opportunities similar to those of a start-up, with the benefits of an established, successful company read on.We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.The Data Extraction Team is a brand new team who plays a crucial role in our organization by designing, implementing, and overseeing advanced web scraping frameworks. Their core function involves creating and refining tools and methodologies to efficiently gather precise and meaningful data from a diverse range of digital platforms. Additionally, this team is tasked with constructing robust data pipelines and implementing Extract, Transform, Load (ETL) processes. These processes are essential for seamlessly transferring the harvested data into our data storage systems, ensuring its ready availability for analysis and utilization.A typical day in the life of a Data Research Engineer will involve acquiring and integrating data from various sources, developing and maintaining data processing workflows, and ensuring data quality and reliability. They collaborate with the team to identify effective data acquisition strategies and develop Python scripts for data extraction, transformation, and loading processes. They also contribute to data validation, cleansing, and quality checks. The Data Research Engineer stays updated with emerging data engineering technologies and best practices. 

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