Intern, Finance Analytics

Constellation Brands•Rochester, NY

21h

About The Position

The Intern, Finance Analytics develops automated solutions for a global organization. The role supports analysis, development, implementation, and scaling of dashboards in a fast-paced enterprise environment, working with BI engineers and stakeholders to deliver analytic data products. It also contributes to reliable data architecture and pipelines, documentation, and issue investigation and remediation.

Requirements

Be pursuing education in Computer Science, Math, Physics, or an equivalent area.
Be a team player who is flexible and outcome-focused.
Demonstrate self-direction, initiative, and willingness to take ownership of projects and tasks.
Have effective oral and written communication skills.
Be committed to finding solutions and enjoy creative problem solving.
Have strong organizational skills and the ability to manage multiple activities in a dynamic, changing environment.
Have strong interpersonal skills and the ability to influence across levels and geographic locations, with awareness of cultural differences.

Nice To Haves

Experience gathering business requirements and translating them into technical details.
Knowledge of SQL and data analysis, and experience with at least one programming language; Python is preferred.
Experience with Git, Jira, and Confluence.
Conceptual knowledge of data and analytics, such as dimensional modeling, ETL, reporting tools, data governance, data warehousing, and structured and unstructured data.
Experience working with data pipelines connected to front-end BI tools such as Tableau, Power BI, or MicroStrategy.
Demonstrated experience managing exceptions and providing support in fast-paced transaction processing environments.

Responsibilities

Collaborate with BI engineers and stakeholders to understand BI needs, gather business requirements, and deliver analytic data products.
Develop and maintain data quality checks to prevent incomplete or inaccurate data and ensure timeliness and consistency.
Produce and maintain data architecture and end-to-end pipelines that follow data engineering principles and business goals.
Create and deliver technical and project documentation using tools such as Jira, Confluence, and Git.
Participate in investigating and remediating issues as needed.
Challenge the status quo and favor simple, high-impact solutions.