BI Functional Analyst

Translate ambiguous business questions into robust data products that teams can trust and act on. As a BI Functional Analyst, you will sit at the crossroads of business strategy and data engineering, shaping the platform capability that turns raw information into decisions.

CONTEXT

Our client, a major player in its sector, is building a data platform capability that must be as clear to business teams as it is robust for technical teams. Business stakeholders arrive with urgent questions about performance, customers, operations, and risk, while data engineers need precise functional direction to build trustworthy pipelines and models. The BI Functional Analyst is the translator in the middle: someone who can listen to a business need, shape it into data requirements, and ensure the final product is accurate, scalable, and genuinely useful. This role is about turning raw data into decisions, and turning vague requests into elegant data products.

ACTIVITIES

Elicit, challenge, and clarify business needs from stakeholders across multiple departments.
Translate requirements into functional specifications, user stories, and data product definitions.
Design and validate data models that support reporting, analytics, and operational decision-making.
Define data quality rules, controls, and acceptance criteria to ensure trustworthy outputs.
Collaborate closely with data engineers, BI developers, architects, and business owners.
Facilitate workshops, interviews, and backlog refinement sessions.
Validate solutions through testing, demos, and user feedback.
Support adoption by documenting data definitions, metrics, and usage guidelines.

EXPECTED ACHIEVEMENTS

Deliver scalable data products that answer real business questions and stand up to scrutiny.
Improve data quality and trust so that stakeholders can act with confidence.
Reduce time-to-insight by bridging the gap between business demand and technical delivery.
Align business and technology teams around a shared understanding of data definitions, priorities, and value.
Establish stronger functional analysis practices within the data platform capability.
Contribute to a data-driven culture where decisions are based on reliable evidence rather than intuition alone.

ENVIRONMENT

Data platform technologies may include SQL, cloud data warehouses, ETL or ELT pipelines, BI tools such as Power BI or Tableau, and data modeling practices.
Methodologies include Agile, Scrum, functional analysis, backlog management, Jira, Confluence, and data governance frameworks.
Stakeholders include business owners, data engineers, BI developers, data architects, product managers, and end users.
The environment values curiosity, structured thinking, clear communication, and a healthy obsession with data quality.