Sr. Manager, Data Analyst

Being on medication is tough enough.
We want to make getting it the easy part
. Getting prescriptions to patients has become increasingly complex. When things get messy along the prescription journey, pharmaceutical manufacturers rely on us to untangle the process and create a clear path—allowing patients to build trusting relationships with their medication brands. We’re not only committed to taking the pain out of the prescription process, but we’re also devoted to bringing the brightest minds together under one roof.

We bring together diverse voices—engineers, pharmacists, customer service veterans, developers, program strategists and more—all with one vision. Each perspective and experience makes Connective Rx better than the sum of its parts. The Senior Manager, Data Analyst plays a pivotal leadership role in driving the organization's data strategy and leading a team of analysts to deliver consistent reporting and impactful insights for Life Science clients, agency partners, and internal stakeholders.

With deep technical expertise and comprehensive domain knowledge of Life Science sponsored messaging, this role influences organizational decisions and leads the design of advanced reporting, dashboarding, and analysis. The Senior Manager acts as a strategic advisor and collaborates with internal and external stakeholders to drive business outcomes through data.
Responsibilities
Core Areas of Focus

• NPI-based reporting (PLD) with a focus on automating, optimizing, and scaling reporting infrastructure.
• Claims-based analyses focused on identifying optimal audiences and assessing impact.
• Self-service reporting solutions that enable technical and non-technical stakeholders to access data that supports business needs.
• Rx impact reporting focused on identifying scalable solutions for complex impact analysis methodologies rooted in claims data.

• Support the development of high-quality reporting with a focus on efficiency, scalability, and advancement through new technologies such as AI-supported tools.
• Oversee the design and execution of complex SQL and Python-based solutions, guiding the team on best practices and scalable approaches. Collaborate with data engineering teams to ensure robust ETL pipelines, data integrity, and adherence to governance and security protocols.
• Lead high-level discussions with senior executives and key stakeholders, clearly communicating complex analytics and their impact on business goals.
• Lead and oversee the analytics team's day-to-day activities, ensuring the successful delivery of multiple concurrent data projects.
• Mentor and coach team members, fostering a culture of continuous improvement and innovation.
• Partner with senior leadership, external clients, and cross-functional teams to identify and prioritize strategic data initiatives. Evaluate and implement emerging technologies to enhance the organization's data analytics capabilities.

• Bachelor's degree in Business, Data Analytics, Information Systems, or a related field required.
• Master's degree in Data Science, Business Analytics, or a related discipline strongly preferred.
• Relevant certifications in SQL, business intelligence tools, or data strategy are preferred.
• Strong problem-solving, leadership, and strategic thinking skills with the ability to align team activities with organizational goals.

• 10–15 years of experience in data analysis, business intelligence, or a related field.
• 3+ years of people leadership experience.
• Proficiency with SQL and Python.
• Experience with AWS cloud-based infrastructure.

• Deep technical expertise and comprehensive domain knowledge to influence organizational decisions and lead the design of advanced reports, dashboards, and analyses.
• Experience managing complex data initiatives, driving business-impacting insights, and mentoring junior team members.

• Advanced SQL skills, including designing and implementing complex database schemas, utilizing CTEs and window functions, and optimizing queries for large datasets.
• Advanced data wrangling skills, including automating data cleaning, managing large datasets, feature engineering, and data…