Data Analyst

Mandatory Skills:

• Programming & analytics: Strong proficiency in Python (and/or SQL) for data analysis.
• Data querying: Strong expertise in SQL for extracting, joining, and transforming data.
• Data modeling & reporting: Good experience designing data models and building reliable reporting structures.
• BI/Dashboarding: Good experience with dashboarding/visualization tools (e.g., Power BI or equivalent).
• Statistical thinking: Solid understanding of descriptive statistics and key analytical methods (segmentation, trends, correlations, basic inference).
• Data quality: Experience implementing data validation checks and ensuring dataset reliability.
• Databases: Good experience working with relational databases such as PostgreSQL (or equivalent).
• Testing mindset: Experience supporting validation/testing for data pipelines (e.g., data checks, unit tests for transformations).
• Collaboration & mindset: Autonomy, technical excellence, clear communication, teamwork, problem-solving, adaptability, curiosity, and continuous improvement.
• Development practices: Familiarity with software/data lifecycle concepts and tools such as Git and Agile processes.

Desired Skills:

• Experience with data warehouses/lakehouses (e.g., Snowflake, Databricks, or similar).
• Experience with time-series analysis, forecasting, or causal impact methods.
• Good experience in preparing technical documentation for datasets, metrics, and analytical workflows.
• Good experience with CI/CD for data pipelines and GitLab CI/CD.
• Experience integrating LLM/AI-enabled analytics (e.g., automated insight generation, structured reporting, or enhanced querying) if applicable to the environment.