Data acquisition lead

As a Data Acquisition Lead, your responsibilities will include planning and driving the Data Acquisition epic, performing analyses, running workshops, collaborating with architects, ensuring alignment with the Infra ART team, gathering requirements for pilot projects, and driving RFP analyses. These tasks are designed to establish a robust common Data Acquisition capability that supports innovative data products.

To apply for the Data Acquisition Lead role, candidates should possess a relevant degree in data science, information systems, or a similar field, along with considerable experience in data acquisition, analytics, and project management. Proficiency in collaborative tools and a firm understanding of data architecture principles will also be crucial.

Collaboration is key for the Data Acquisition Lead. You will closely coordinate with the Infra ART team to implement infrastructure components, while also partnering with the Platform Modernization team to align activities, timelines, and dependencies essential for successful data acquisition.

As a Data Acquisition Lead, you will initiate and oversee critical projects focused on enhancing our data acquisition processes. This includes selecting pilot projects, performing analyses, and driving RFPs, all geared towards establishing a cohesive data strategy that supports our new data products.

Yes, experience in data architecture is highly beneficial for the Data Acquisition Lead position. A solid understanding of data frameworks and the ability to work collaboratively with architects will ensure you can effectively drive initiatives and align with the company's data strategy.

Share specific examples from previous roles where you managed or improved data acquisition processes, including any frameworks or methodologies you employed to enhance efficiency.

Discuss your method of engagement, emphasizing the importance of open communication and active listening to ensure that project goals align with the architectural vision.

Select a project that highlights your problem-solving skills, detailing the challenges faced, how you overcame them, and the results achieved.

Mention any specific tools you have experience with, like SQL or Python, and discuss methodological approaches you find effective, such as agile methodologies or design thinking.

Explain your approach to prioritization, possibly mentioning techniques like the Eisenhower Matrix or Agile Scrum to maintain focus on critical tasks.

Talk about your strategies for regular communication and alignment meetings to keep all stakeholders in sync with project timelines and dependencies.

Outline the steps you would take to conduct an RFP analysis, including stakeholder engagement, criteria assessment, and making evidence-based decisions.

Share insights on current trends such as automation, real-time data processing, or AI-driven analytics, and how you see them influencing the future of data acquisition.

Give a real-world example, demonstrating your communication skills and your ability to present data-driven arguments to persuade others.

Discuss the essential functions of data architecture, including ensuring data integrity, optimizing data flow, and supporting the broader business objectives of data acquisition.