Senior Manager, Data Acquisition

Datassential•,

1d•Remote

About The Position

Datassential is a leading global intelligence platform for the food and beverage industry. Leveraging billions of data points and cutting-edge AI, we provide a suite of innovative solutions that empower more than 90% of the world’s largest food and beverage brands to develop, market, and sell their products more effectively. Based in Chicago, USA, Datassential has expanded its global reach through strategic acquisitions of CHD Expert (France) in 2022 and Brizo Data, Inc. (Canada) in 2025. In 2024, we secured investment from top-tier private equity firms New Mountain Capital and Endicott Capital—a milestone that fuels our accelerated product roadmap and strengthens our research and development, enabling us to deliver even greater value to our clients. Our remote-first, globally distributed team thrives on diverse perspectives and deep expertise in the food and beverage space. Food brings people together—and at Datassential’s table, there’s room for everyone. Data is the foundation for everything we deliver at Datassential, and expanding and improving our data sources is of central strategic importance to our company and the customers we serve, who include some of the biggest brands in the food industry. Foodservice is a complex and nuanced data landscape, and you will have the opportunity to think creatively about how to expand the insights we can deliver on a global basis. We are passionate about data, committed to doing the work well, and have a ‘we can do anything’ attitude. We value work-life balance, and you will be joining a team and company that wants you to grow.

Requirements

5-8 years of experience in data acquisition, data operations, data vendor management, or a related data management function, including 3+ years directly managing a team
Demonstrated experience sourcing, evaluating, and onboarding third-party data providers, including negotiating licensing and usage terms
Experience owning or supporting management of a budget or cost center: building forecasts, tracking actuals against plan, and reporting variance to stakeholders
Ability to build and apply a make-vs-buy framework — internal collection vs. third-party sourcing — weighing cost, coverage, quality, and timeliness
Experience managing vendor relationships post-contract, including quality issues, corrective action plans, and renewal negotiations
Working understanding of data quality concepts (coverage, accuracy, freshness) sufficient to define and track KPIs against them
Fluency in hands-on data analysis and working directly with data to evaluate consistency and quality
Familiarity with data ingestion/ETL pipelines and how new sources get onboarded technically (APIs, file feeds, scraped data)
Interest in and awareness of AI/automation tools relevant to data collection, with the judgment to evaluate cost-benefit tradeoffs
Track record managing stakeholders across Product, Engineering, Data Operations, Legal, and Finance
Strong negotiation skills, with examples of favorable outcomes in vendor or partnership discussions
Clear, proactive communicator — able to report on plan variance, escalate risk, and align teams around priorities

Nice To Haves

Domain experience in foodservice, food & beverage, hospitality, or adjacent consumer industries
Familiarity with Alteryx or other low-code ETL environments
Proficiency in SQL across one or more environments
Familiarity with web scraping as a data collection method
Familiarity with project management tools such as Jira/Confluence

Responsibilities

Lead the sourcing and collection of data to support Datassential applications, research, and insights analysis globally.
Manage the data collection across a variety of forms and collection channels, including data collected directly via internal scraping operations as well as from external third party service and providers.
Work with Datassential senior leadership to identify strategies for building proprietary data assets in support of company objectives.
Identify new data sources, manage negotiations of terms with new third party providers, and work with Product, Engineering, and Data Operations teams to coordinate data onboarding and ingestion.
Manage data vendor and partnership relationships, ensuring that requirements for downstream use are met.
Lead corrective actions as well as innovation efforts to ensure quality and efficiency of collected data.
Interact directly with data to assess data relevance, sufficiency, and quality.
Define and track costs against budget for data acquisition, and work with data operations and finance and accounting teams to ensure cost efficiency and predictability.
Manage an internal team responsible for data scraping operations, coordinating scraping maintenance and execution to support continuous and timely collection of foodservice industry, operator and menu data.
Coordinate and work with the Data and Product teams as well as other global stakeholders to identify and evaluate sources for new data elements and improved sources for existing data elements.
Own the determination of the best source or process for data collection, presenting options to stakeholders and promoting the correct balance of cost, quality, coverage, and timeliness to meet the needs of the business.
Manage decisions on the use of internal scraping vs third-party sourcing.
Lead the onboarding of new third-party data sources, negotiating terms favorable to Datassential and aligned with business, financial, legal, and data usage objectives.
Work with Engineering and other Data Team members to set up data collection and ingestion processes for new data sources.
Determine the most appropriate, advantageous and cost-effective use of AI and other technologies in data collection to deliver expanded and improved data.
Manage the budget determination for data collection, track and report actuals against budget, and take action to ensure budget alignment.
Ensure successful achievement of expected data collection cycles, and manage internal stakeholder communication on variance to plan.
Manage a team providing scraping script creation and maintenance, coordinating their work, and ensuring responsiveness and communication regarding issues in data scraping that will impact customers.
Collaborate with the Product team and other key stakeholders to align data collection projects and timing with the product roadmap.
Collaborate with senior leadership on strategic planning for data asset growth.
Identify and track KPI’s on the coverage, quality, cost, and speed of data collection.
Communicate progress in improvement of these metrics.