Capco logo
Capco

Capco, a Wipro company, is a management & technology consultancy dedicated to the financial services & energy industries

Desenvolvedor Power BI, Analytics Pleno

Software EngineerSoftware EngineerFull TimeRemoteSeniorTeam 1,001-5,000Since 1998H1B SponsorCompany SiteLinkedIn

Location

Brazil

Posted

4 days ago

Salary

0

Seniority

Senior

Bachelor DegreePortugueseAzureETLPySparkPythonSparkSQLSSIS

Job Description

Desenvolvedor Power BI, Analytics Pleno

Capco

• Projetar, construir e operar soluções corporativas em Microsoft Fabric (lakehouse) e Power BI voltadas para analytics de marketing e clientes. • Responsável pela entrega de ponta a ponta: ingestão e orquestração (Fabric Data Factory), transformações com Spark (PySpark/Spark SQL), modelagem lakehouse no padrão medallion (Bronze/Prata/Ouro), desenho de modelos semânticos e otimização de performance no Power BI. • Experiência sólida em ambientes produtivos com cargas incrementais/CDC, validações de qualidade de dados, segurança (RLS), monitoramento/alertas e práticas de implantação Dev/Test/Prod.

Job Requirements

  • Power BI (Desktop e Service/Fabric): modelagem semântica, DAX, Power Query (M), construção de dashboards executivos, otimização de performance, governança e publicação.
  • Microsoft Fabric: conceitos e prática com OneLake/Lakehouse, Semantic Models (datasets), pipelines e consumo analítico na plataforma.
  • Databricks (Azure Databricks): notebooks, SQL Warehouses, consumo por Power BI, noções de arquitetura e boas práticas de processamento analítico.
  • ETL-ELT Experiência sólida em ETL/ELT, automação de ingestão e integração de múltiplas fontes.
  • ETL-ELT Ferramentas: PowerCenter OU SSIS OU Azure Data Factory (ADF) (pelo menos uma com domínio e as demais como conhecimento aplicável).
  • Bancos de SQL Avançado: joins complexos, CTE, window functions, agregações, modelagem para performance e qualidade de dados.
  • Modelagem de Data Warehouses (Star Schema / Snowflake), camadas de dados e desenho de modelos para analytics e BI.
  • Python/PySpark para automação, tratamento/validação de dados, apoio a ETL/ELT e análises; boas práticas de organização e reuso - Intermediário.
  • Noções de Ciência de Dados Conceitos fundamentais: estatística básica, features, validação, leitura de modelos e aplicação em contexto de negócio.

Benefits

  • Promovemos uma cultura inclusiva
  • Valorizamos a diversidade em todas as suas expressões

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