Power BI Analyst (Data Modeling + Visualization)

📍LATAM - 100% Remote

🤝Contract - USD

🗣️Advanced English skills is required

Role Summary

Architect and maintain certified semantic datasets and dashboards in Power BI and Sigma. Serve as a “BI engineer” who ensures that reports are accurate, fast, and trustworthy by design.

Key Responsibilities

• Semantic Data Models: Design and implement data models (star schemas, dimension tables,

  fact tables) for BI. Create version-controlled datasets (in Power BI or Sigma) with standardized

  KPI definitions, row-level security, and clear lineage. Ensure each model is documented (schema

  diagrams, data dictionaries) and reusable by analysts.

• Dataset Quality Gates: Develop automated pre-publish validations for datasets: check row

  counts, data freshness, and parity of calculated metrics against source references. Surface

  validation statuses on dashboards (e.g. “data verified” badges) to reassure consumers.

  Implement CI/CD for BI artifacts (e.g. Git-driven deployment of PBIX or Sigma assets).

• Dashboard Development: Build executive scorecards and dashboards (audience engagement,

  revenue/attendance, operational metrics). Embed telemetry to track report usage and

  performance. Periodically prune or optimize dashboards to remove redundancy and improve

  query efficiency.

• Expose QA Insights: Incorporate data quality test results (e.g. pass/fail indicators from Data

  Quality Engineering) into visual reports. Partner with data engineering and DQE teams to align

  data contracts and measurement tests with BI reports.

• Training & Governance: Train analysts on model best practices (efficient queries, modular

  design). Create guidelines for when to extend existing models vs. build new ones. Document all

  models, dashboards, and processes in Confluence or via a BI portal.

Core Technical Skills

• Power BI: Advanced skills in Power BI Desktop (Power Query/M, DAX) and Power BI Service.

  Ability to implement incremental refresh, aggregations, and optimization techniques for large

  datasets.

• Sigma Computing: Experience with building and securing Sigma data models (joins, parameters,

  row-level security) and writing efficient SQL behind the scenes.

• SQL & ETL: Strong SQL (Snowflake or similar) for transforming and loading data. Familiarity with

  data transformation tools (dbt, Azure Data Factory).

• Validation Automation: Ability to script or schedule dataset validation checks (e.g. via Python or

  SQL jobs). Understanding of CI/CD pipelines for BI (Azure DevOps, GitHub Actions).

• Analytics Tools: Basic knowledge of web analytics (GTM, GA4) is helpful for tracing metric

  origins. Understanding of UTM parameters and attribution is a plus.

• Tools & Collaboration: Use Jira/ServiceNow for BI project tracking and issue management.

  Maintain detailed documentation (Scribe, Confluence) for data models and report usage.

Nice-to-Have:

• Experience with other BI platforms (Tableau, Looker) or semantic layers (Power BI Analysis

  Services).

• Knowledge of advanced data modeling (Data Vault, Kimball methodology).

• Familiarity with SQL database tuning and indexing to improve query speed.

• Skills in UX design for dashboards (ensuring visual best practices and accessibility).