Data Analyst – BI & Analytics Mid/Senior-Level

WAMGROUP

. Create, maintain, and enhance dashboards, KPIs, and management reports .

Posted 9/17/2026full-timeGoiânia • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in SQL for data analysis and processing, along with strong capabilities in developing and maintaining ETL/ELT processes. Proficient in creating and enhancing dashboards and KPIs using Power BI or similar tools, while ensuring data quality and governance.

Highest-signal resume keywords

SQL QueryingETL/ELT ProcessesData ModelingPower BIData Quality

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

SQLData ModelingETLData TransformationData CleansingData ValidationData IntegrationData ArchitectureData AnalysisData Pipeline Development

Soft Skills

Analytical SkillsCommunication SkillsProblem-SolvingCollaborationAutonomy

Tools & Technologies

Power BIDatabricksAPIsData LakeLakehouse

Industry Keywords

KPI DevelopmentData GovernanceData Quality Best PracticesBusiness Process TranslationData Environment Organization

Tech Stack

Tools & technologies

ETLPythonSQL

About the role

Key responsibilities & impact

Create, maintain, and enhance dashboards, KPIs, and management reports
Develop and structure KPIs for different areas of the company
Gather and understand requirements in collaboration with business teams
Translate business needs into analytical solutions and data structures
Extract, clean, organize, transform, and validate data from different sources
Develop SQL queries for data analysis, processing, and preparation
Build and enhance data models for BI and Analytics
Develop and maintain ETL/ELT processes
Support the creation, maintenance, and enhancement of data pipelines
Integrate information from databases, APIs, files, and corporate systems
Structure processes for collecting, storing, processing, and making data available
Support the organization and evolution of the Data Lake and Lakehouse environment
Contribute to the structuring and use of Databricks
Automate processes for collecting, processing, and making information available
Conduct exploratory analyses to identify patterns, trends, deviations, and opportunities
Investigate discrepancies and inconsistencies across different data sources
Ensure the consistency, quality, and reliability of the information made available
Define and document KPIs, business rules, sources, models, and data processes
Support the definition of standards and best practices for data usage
Identify opportunities to improve the architecture, processing, and delivery of information
Work collaboratively with Systems, Technology, and various business teams
Contribute to building and evolving WAM’s data environment by connecting technology, data, and business needs

Requirements

What you’ll need

Experience with Power BI or an equivalent data visualization and analytics tool
Strong ability to create, organize, and enhance dashboards and KPIs
Solid SQL knowledge for querying, processing, transforming, and analyzing data
Experience with data modeling
Knowledge of data processing, cleansing, transformation, and validation
Knowledge of ETL/ELT processes and concepts
Experience integrating different data sources
Knowledge of relational databases
Ability to structure processes for collecting, transforming, storing, and making information available
Knowledge of data environment organization and architecture
Ability to investigate and resolve data-related issues
Strong analytical and information-interpretation skills
Ability to understand business processes and translate them into data solutions
Strong communication skills for interacting with technical and business teams
Ability to document data processes, sources, rules, and structures
Autonomy in managing requests and investigating issues
Preferred: experience with or knowledge of Databricks
Preferred: knowledge of Data Lake and Lakehouse architecture
Preferred: experience building and maintaining data pipelines
Preferred: experience with APIs and integrations between different systems
Preferred: knowledge of data quality and governance best practices
Preferred: experience organizing or enhancing corporate data environments
Preferred: knowledge of processing and storing large volumes of data
Preferred: experience automating data-related processes
Preferred: knowledge of Python applied to data
Preferred: knowledge of data versioning, orchestration, or transformation tools

Benefits

Comp & perks

No additional benefits, perks, or compensation are explicitly stated in the job posting