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About the role

This position is responsible for transforming raw information into decisions that shape organizational outcomes in a precise and reliable manner. The data curator will work alongside business teams to convert complex data into actionable insights that drive measurable value. Success in this role requires ownership of data quality, integrity, and documentation to support downstream analysis and decision-making. The individual in this role acts as a steward of data, ensuring that datasets are well-structured, consistent, and trustworthy for all users. Collaboration with analysts, data scientists, and engineers will be essential to align data definitions with business logic and operational needs. This role directly supports the development of metrics that reflect real-world performance and strategic priorities. The data curator ensures that the underlying data foundations enable accurate reporting and informed decision-making across the organization. By maintaining rigorous standards for data organization and clarity, this role contributes to the long-term scalability and usability of analytical assets.

Key facts

What you'll do

Analyze databases and datasets to uncover meaningful patterns that inform business decisions.

Synthesize analytical findings into clear dashboards that guide operational decisions for stakeholders across the organization.

Construct metrics aligned with real operational needs to support business questions and validate strategic priorities.

Track progress over time by developing and maintaining metrics that reflect changes in business performance and user behavior.

Confirm academic readiness for future responsibilities by meeting the stated degree requirements outlined in the listing.

Ensure applications submitted through the official channel are considered during matching events for relevant data roles.

Maintain data documentation that supports transparency, reproducibility, and clarity for both current and future analyses.

Partner with stakeholders to understand data requirements and translate business needs into structured data definitions.

Support the implementation of data pipelines that enable efficient movement and storage of information for analysis.

Promote data literacy by communicating insights in a clear and actionable manner to non-technical members of the organization.

Contribute to the continuous improvement of data collection processes to enhance reliability, usability, and coverage of datasets.

Act as a central point of contact for data-related inquiries, ensuring consistency in definitions and interpretations across teams.

Requirements

A bachelor's degree is required, and the specific field must be confirmed The listing states this academic prerequisite to confirm that candidates are prepared for the responsibilities associated with data curation and analysis.

Submission through the official apply page is necessary to be reviewed during matching events for relevant opportunities.

This step is mandatory to advance in the process and be considered for full-time positions in data.

Candidates must demonstrate attention to detail and the ability to manage complex datasets with accuracy and consistency.

Strong written and verbal communication skills are required to explain analytical concepts to both technical and non-technical audiences.

Basic familiarity with database concepts and data modeling principles is necessary to support effective collaboration with engineering teams.

The ability to work independently and as part of a cross-functional team is essential in a fast-paced, data-driven environment.

Practical notes

Poland is the location for this full-time engagement.

Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Questions to ask

Good questions to ask the employer in the interview include what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made.

Asking about growth paths and the review process is also well received, as it shows long-term interest in the role.

Employers expect thoughtful questions, and good ones demonstrate preparation and curiosity about the position and the company.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels as strategic ownership increases. The field changes quickly, so continuous learning is part of the job for any data professional. Those who can translate numbers into decisions tend to advance fastest within data-driven organizations. Building a strong portfolio of analyses and clear documentation supports long-term career development in this field.

About the company

Brainly is the #1 AI education tool in the world, with a vision to give every student in the world access to personalized learning, no matter their background or resources. Powered by its full-service AI Learning Companion™, Brainly is relied upon by millions of students, parents and teachers every day for personalized, on-demand academic assistance.