Pessoa Especialista Data Platform Engineer

Há 2 dias

Ribeirão Preto, Brasil Gruposbf Tempo inteiro

Job description O esporte nos move e acreditamos no seu poder de transformar vidas. Estamos construindo um ecossistema para integrar a experiência do atleta amador, profissional ou ocasional, aquele que busca o esporte por bem-estar, diversão ou como estilo de vida. Esse Grupo, que segue em constante expansão para os apaixonados por esporte, conta hoje com a Centauro, a maior varejista esportiva multimarcas da América Latina, a Fisia, com a distribuição oficial da marca Nike no Brasil, a FitDance, referência no ensino e prática de dança, a NWB, a maior produtora de conteúdo de esporte na internet, a OneFan, que conecta clubes de futebol a torcedores e a X3m, de sportainment com grandes eventos esportivos em seu portfólio. Todos têm lugar em nosso time Nós queremos ser referência para toda e qualquer pessoa que pensar em esporte no Brasil. E aí, que tal vestir a nossa camisa? #SomosSBF Main responsibilities Buscar inspiração no mercado para trazer novas ideias que possam ser utilizadas para melhorar a plataforma de dados; Atuar ativamente na detecção e na solução de problemas, oportunidades e melhorias relacionados à disciplina de dados na tecnologia; Garantir que o time esteja alinhado com evolução da plataforma e todos entendam as motivações por trás delas; Identificar e antecipar impactos das abordagens em outros produtos cross-squads; Trazer a visão do todo, ao colaborar com o planejamento, acompanhamento e organização de uma dada iniciativa que visa onde outro analista, seja responsável, até a entrega de valor, ajudando a mapear os possíveis riscos e impactos; Orientar, engaja e fomenta proativamente a cultura data driven em toda a Empresa. Requirements and skills Graduação em Ciência da Computação, Engenharia da Computação, Sistemas de Informação ou área relacionada; Python; SQL; Conceitos de administração de banco de dados; Conceitos de DW; Shell; Alguma ferramenta/linguagem de IaC: terraform, ansible, puppet; Conceitos de infraestrutura (rede, disco, cpu...); Proficiência com containers (docker, kubernetes); Conceitos de engenharia de software (protocolos de API, SoC, SOLID e etc); Conceitos de sistemas com uso intensivo de dados: lakehouse, data lake, DW MPP; Proficiência com ferramentas de processamento em streaming: kafka, spark, flink; Conceitos de streaming de dados: hopping, session, tumbling; Proficiência com bancos nosql: mongo, cassandra (scyllaDB), druid Conceitos de arquiteturas de sistemas distribuidos: ring, master/worker; Conceitos de machine learning: treino, serving, feature, reinforcement learning; Proficiência com infraestrutura em cloud. #J-18808-Ljbffr

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