Remote Jobs at Semantix
Find your next remote opportunity · 9 Open Positions
About
We are a reference when it comes to Big Data, Analytics, and Artificial Intelligence, developing innovative and disruptive solutions, besides AI platforms in the “one-stop-shop” model, allowing the implementation of complex data environments in a few minutes.
From a multi-cloud infrastructure to advanced business performance and data governance solutions for all industries.
Founded in 2010 in Brazil, and now present all over the American continent, Semantix develops data-driven solutions so that our customers will always be one step ahead.
Data Engineer, Mid-level
Semantix
Data Engineer responsible for developing scalable data pipelines using modern technologies like Azure and Databricks. Join Semantix to impact billions of lives with data-driven solutions.
Engenheiro de Dados Sênior
Semantix
Senior Data Engineer developing and supporting scalable cloud data environments at Semantix. Focused on data pipelines and distributed processing with modern technologies.
Senior Data Scientist
Semantix
Develop and deploy ML and LLM models at Semantix, handling large-scale data and MLOps. Collaborate with engineering, product and BI to deliver actionable insights.
Senior Scrum Master
Semantix
Scrum Master leading data engineering and science squads at Semantix. Facilitating agile ceremonies and improving delivery for Bradesco data projects.
Engenheiro de Dados Pleno
Semantix
Pleno Data Engineer building ETL pipelines, Databricks, PySpark, Azure at Semantix. Deliver reliable, efficient data platforms for business analytics.
Engenheiro de Dados Sênior, MongoDB
Semantix
Lead ETL development, Databricks and PySpark pipelines for Semantix's Big Data and AI projects. Collaborate with business to deliver data that drives decisions.
Senior Data Engineer, MongoDB
Semantix
Senior Data Engineer at Semantix developing ETL, MongoDB and Databricks pipelines to deliver business data
Engenheiro de Dados Sênior
Semantix
Engenheiro de Dados sênior na Semantix. Desenvolver e otimizar pipelines, ETL, modelagem e qualidade de dados para projetos de Big Data.
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