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Open nowPosted 66 days ago

Analista de Dados Junior

ALIFE NINO91 open roles

Where
São Paulo, BR
Work mode
On site
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Your applicationOpen nowAnalista de Dados JuniorALIFE NINO · São Paulo, BR

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on ALIFE NINO's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. ALIFE NINO postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 66 days ago

ALIFE NINO median: 2 days open

The posting

Se você é apaixonado(a) por dados, gosta de transformar informações em insights estratégicos e quer aprender na prática como os dados apoiam a tomada de decisão em um grupo dinâmico de bares e restaurantes, essa vaga é para você! Você vai atuar junto ao time de dados, construindo e mantendo dashboards, tratando dados de múltiplas fontes e apoiando a operação e a gestão com análises confiáveis.

Atribuições

- Construir e manter dashboards, relatórios e indicadores gerenciais no Power BI;

- Construir consultas SQL para extração, manipulação e cruzamento de dados;

- Coletar, tratar e consolidar dados de diferentes fontes, garantindo qualidade e consistência das informações;

- Apoiar a área de Gestão no desdobramento e acompanhamento de metas e KPIs do negócio;

- Apoiar as rotinas de dados e pipelines sob orientação do time;

- Documentar regras de negócio, métricas e processos de BI;

- Apoiar o levantamento de requisitos junto às áreas de negócio;

- Comunicar resultados de forma simples e visual para públicos não técnicos;

- Identificar oportunidades de melhoria e contribuir com automações de rotina.

Requisitos

- Cursando ou formado(a) em TI, Engenharias, Estatística, Economia, Ciência de Dados, Sistemas de Informação ou áreas correlatas (Exatas);

- Conhecimento intermediário em SQL (SELECT, JOINs, agregações e filtros);

- Conhecimento intermediário em Excel;

- Conhecimento em Power BI para construção de dashboards e relatórios;

- Boa comunicação e vontade de aprender sobre o food service.

Diferenciais

- Noções de Python para análise de dados (pandas);

- Conhecimento avançado em Excel;

- Noções de modelagem de dados;

- Noções de versionamento com Git;

- Uso de ferramentas de IA generativa para acelerar consultas e documentação.

Vale Transporte ou Auxílio Mobilidade em cartão flexível Vale Refeição Assistência Médica Hapvida - sem desconto mensal, apenas coparticipação quando utiliza, podendo acrescentar até 1 dependente (cônjuge ou filho) Seguro de Vida - sem desconto para o colaborador TotalPass

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One press. We do the rest.

  1. A CV for this posting

    Written against ALIFE NINO's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on ALIFE NINO's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    ALIFE NINO's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

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  6. The interview in your calendar

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    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
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Why it works

3×

more interviews than doing it yourself with ChatGPT.

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  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

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The numbers game

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