SR Analyst, Data Management

BoehringerPRD•Duluth, GA

10d

About The Position

As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies' success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees. The Sr. Reporting Analyst, Data Management plays a critical role in enabling data-driven decision-making by partnering closely with business stakeholders to translate data into actionable insights. This role operates at the intersection of business and data, working with diverse and evolving datasets while engaging stakeholders to understand requirements, shape reporting solutions, and deliver meaningful insights that drive business performance. This is a hands-on, collaborative role ideal for someone who enjoys working with both data and people - bringing structure to complex data and clarity to business questions.

Requirements

Bachelor’s degree in Data Analytics, Statistics, Information Systems, Business, Computer Science, or related field.
5+ years of experience in a data analyst, reporting analyst, or BI analyst role or Master’s degree with 3+ years of relevant experience.
Strong attention to detail, documentation discipline, and comfort working through ambiguity.
Solid communication skills; able to explain data issues and logic to both technical and non-technical partners.
Proven ability to gather and translate business requirements into reporting and analytical solutions.
Must be legally authorized to work in the United States without restriction.
Must be willing to take a drug test and post-offer physical (if required).
Must be 18 years of age or older.

Nice To Haves

Experience with BI/visualization tools (Power BI, Tableau, Alteryx, etc.).
Strong data manipulation skills (SQL, Excel; Python or R is a plus).
Experience working with commercial, retail, or pharma data.
Familiarity with cloud data platforms (AWS, Snowflake, or similar).
Experience with data validation, UAT, and QA processes.

Responsibilities

Curate and prepare datasets to support business reporting and analytical needs.
Develop dashboards, reports, and analytical outputs that provide clear and actionable insights.
Identify trends, opportunities, and risks to support strategic and operational decisions.
Partner with stakeholders to define and refine KPIs, metrics, and performance views.
Ensure outputs align with how the business views performance across accounts, products, and channels.
Work with structured and unstructured data from multiple sources (e.g., Excel, databases, reporting tools)
Profile, clean, and standardize data to ensure accuracy, consistency, and usability
Develop proof-of-concept analyses and reporting views to demonstrate insight potential.
Translate findings into clear requirements for scalable reporting and data solutions.
Collaborate with data engineering teams to operationalize reporting datasets and pipelines.
Partner with cross-functional stakeholders (sales, commercial excellence, finance) to understand business objectives, challenges, and reporting needs.
Gather, document, and refine business requirements for reporting and analytics solutions.
Translate business questions into data requirements, analytical approaches, and reporting outputs.
Act as a trusted advisor by providing data-driven recommendations to support decision-making.
Build strong working relationships and proactively engage stakeholders to align priorities and outcomes.
Work closely with data engineers and product teams to deliver high-quality, scalable reporting solutions.
Participate in agile ceremonies (stand-ups, backlog refinement, sprint reviews).
Support testing, validation, and continuous improvement of reporting outputs and data pipelines.
Drive improvements in reporting processes, data quality, and stakeholder communication.