Power BI & Sigma Analyst (Data Modeling + Visualization)

Formamos parte de una organización dinámica y flexible con gran capacidad de adaptación y compromiso. Valoramos las competencias, habilidades, experiencia y potencial de las personas, así como sus cualidades personales, aplicando dichos valores tanto a nuestro trato con los clientes como entre nosotros.

We’re looking for a BI Analyst / Engineer to design and maintain semantic data models and high-quality dashboards in Power BI and Sigma. You’ll ensure reporting artifacts are governed, validated, and optimized for scale—empowering teams to trust the data from day one.

Key Responsibilities

Semantic Data Modeling : Design star schemas, fact / dimension tables with consistent KPIs, RLS (row-level security), and complete documentation (schemas, lineage, data dictionaries). Make models modular and reusable.

Automated Validations : Build pre-publish checks on row counts, freshness, and metric parity. Display validation status on dashboards. Implement CI / CD pipelines for BI asset deployment (PBIX, Sigma, etc.).

Executive Dashboards : Develop high-impact reports across revenue, attendance, engagement, and ops metrics. Monitor usage, embed telemetry, and continuously optimize or deprecate unused assets.

QA Visibility : Integrate data quality test results (e.g., pass / fail flags) into reports. Work with Data Engineering and DQ teams to align tests and data contracts with the BI layer.

Training & Governance : Coach analysts on model extensions, best practices, and efficient queries. Maintain full documentation in Confluence or a BI catalog / portal.

Core Technical Skills

Power BI : Advanced use of Power BI Desktop (DAX, M / Power Query) and Service. Familiarity with aggregations, incremental refresh, performance tuning.

Sigma : Strong understanding of joins, filters, parameters, and RLS. Comfortable writing performant SQL queries.

SQL & ETL : High proficiency in SQL (e.g., Snowflake) and data pipelines (dbt, Azure Data Factory).

Validation Automation : Ability to script and schedule validation logic using Python or SQL. Knowledge of CI / CD for BI (Azure DevOps, GitHub Actions).

Analytics : Familiarity with GA4, GTM, UTMs, and attribution tracking.

Collaboration & Docs : Use Jira / ServiceNow for project tracking. Maintain clear, reusable documentation (Confluence, Scribe, etc.).