Business Intelligence Analyst

Transform data into actionable business insights that support informed decision-making by assisting the Business Intelligence team with business problem analysis, reliable reporting, and continuous improvement of data quality and availability.

This role has a strong analytical, logical, and technical focus. The ideal candidate is expected to develop the ability to understand business challenges, formulate hypotheses, validate them using data, and continuously iterate based on findings. The position also offers a clear growth path toward data integration and automation responsibilities, making an interest in technical data engineering and automation highly valuable.

• Build and maintain reports and dashboards that support operational and strategic business decisions.
• Extract, clean, structure, validate, and prepare data for analysis while ensuring consistency and accuracy.
• Support business problem analysis by developing hypotheses, validating assumptions, and presenting data-driven insights.
• Map and document business processes related to data generation and usage, identifying opportunities to improve data quality, reliability, and efficiency.
• Respond to ad hoc reporting and analytical requests from multiple business areas by translating business needs into actionable data requirements.
• Document data sources, calculation logic, and analytical processes to ensure transparency, continuity, and traceability.
• Identify manual or repetitive reporting tasks and contribute to automation initiatives.
• Collaborate with the Business Intelligence team on projects aimed at improving data infrastructure, governance, and overall data quality.

• Ability to query and manipulate data using SQL, including writing queries with filters, aggregations, and table joins (JOINs) to retrieve and prepare information.

• Advanced Microsoft Excel skills.
• Experience with at least one Business Intelligence tool (preferably Power BI), including connecting to data sources, building reports and dashboards, and presenting insights.

• Solid understanding of programming fundamentals, including functions, data structures, error handling, and modules.
• Ability to read, understand, maintain, and extend existing Python code, including object-oriented code using classes and objects.

• Strong logical, mathematical, and computational reasoning skills.
• Ability to break down complex problems, analyze data systematically, and validate results.
• Understanding of descriptive statistics, including averages, medians, distributions, and percentage variations.

• Experience cleaning, structuring, and validating datasets.
• Ability to identify inconsistencies, duplicate records, missing values, and outliers.

• Ability to communicate analytical findings clearly to both technical and non-technical audiences.
• Experience documenting methodologies, assumptions, and analytical processes.

• Experience with low-code automation tools such as Power Automate, n8n, Make, Zapier, or similar platforms.
• Basic understanding of system integrations and API consumption.
• Familiarity with data modeling concepts, including fact tables, dimension tables, and dimensional schemas.
• Exposure to cloud-based data platforms such as BigQuery, Databricks, Supabase, Snowflake, or similar technologies.
• Basic knowledge of version control using Git/GitHub.
• Understanding of formal process modeling methodologies such as BPMN or equivalent.
• Coursework, certifications, or specialized training in Data Analytics, Power BI, SQL, or Python.
• Portfolio showcasing academic, personal, or professional data projects.

• Analytical Curiosity – Genuine interest in understanding the "why" behind the numbers and challenging assumptions.
• Structured Thinking – Ability to organize information, prioritize effectively, and solve complex problems methodically.
• Clear Communication – Ability to translate technical findings into practical business recommendations.
• Attention to Detail – Strong focus on validating data and ensuring reporting accuracy, recognizing the business impact of incorrect information.
• Self-Learning – Initiative to independently learn new tools, technologies, and analytical techniques.
• Collaboration – Ability to work effectively with cross-functional teams and actively incorporate feedback.
• Ownership & Accountability – Commitment to meeting deadlines while delivering high-quality, reliable work.

Senior-year student, recent graduate, or graduate in one of the following fields:

• Computer Systems Engineering
• Computer Science
• Industrial Engineering
• Business Engineering
• Business Administration Engineering
• Mathematics
• Statistics
• Or a related quantitative discipline.

1 year of experience in Data Analytics, Reporting, Business Intelligence, or related roles.

Relevant internships, academic projects, and personal portfolios will also be considered.

• English proficiency at B2 level, with the ability to read technical documentation and actively participate in workplace conversations.