553 Big Data jobs available for remote work from home. Apply for positions such as Estágio em Engenharia de Análise de Dados - Vaga afirmativa para pessoas LGBTQIAPN+, Estágio em Engenharia de Análise de Dados - Vaga afirmativa para mulheres cis e trans, AWS Engineer - Senior Associate, AI & Data, Technology Consulting, and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The intern will join the Data and Consulting team, helping clients transform their data strategy by applying advanced analytics to generate business insights from big data and AI. Responsibilities include supporting data analysis, exploring data patterns, assisting with reports and dashboards using BI tools, and manipulating data via SQL.
The intern will join the Data and Consulting team, applying advanced analytics to big data and AI to generate business insights for clients. Responsibilities include supporting data analysis, exploring data patterns, assisting with reports/dashboards using BI tools, and manipulating data via SQL.
The AWS Engineer will design, build, and maintain scalable data pipelines and analytics platforms on AWS. This includes transforming raw data into analytics-ready datasets and ensuring data quality and compliance.
The Software Architect will define and evolve cross-team architecture for data platforms and services, focusing on schema design and interoperability. They will collaborate with various teams to ensure the seamless flow of AEC data throughout the lifecycle of built assets.
The Senior Developer will design and build cloud-native, event-driven data and analytics services on AWS, focusing on serverless application development and ETL pipelines. They will collaborate with data, analytics, and product teams to deliver reliable, scalable data services and BI capabilities.
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The Data Analyst will collect, clean, and analyze supply chain data to identify trends and optimize operations. They will create dashboards and reports to present actionable insights and collaborate with cross-functional teams to provide strategic recommendations.
The Data Engineer will design, develop, and maintain scalable ETL pipelines and data workflows to ingest and transform data into modern cloud platforms, primarily utilizing Azure Databricks and lakehouse architectures.
The Data Analyst will manage and analyze large volumes of daily financial data and design, implement, and continuously improve data quality frameworks. They will also build and maintain dashboards and reports for business insights.
The role involves driving the adoption and growth of the FICO Platform by educating customers on its capabilities. It requires building relationships with senior stakeholders and collaborating with internal teams to deliver effective solutions.
Build and nurture relationships with senior client stakeholders to address their business challenges while leading high-stakes negotiations for multi-million-dollar contracts. Develop and execute comprehensive business plans that drive account expansion and profitability.
The Databricks Developer will build and maintain data pipelines using Apache Spark on Databricks and ensure data handling follows security and governance standards. They will also investigate and fix issues in production environments.
The role involves evolving and innovating Netflix's data infrastructure and building scalable, highly available distributed systems. Engineers will collaborate across teams to solve complex challenges and contribute to open source communities.
The Data Analytics Engineer analyzes complex customer data to determine integration needs and develops scalable data integration pipelines. They also collaborate with various teams to align solutions with business objectives and automate data validation processes.
The Senior Application Architect will oversee multiple teams of developers and applications, ensuring that software meets client expectations for quality and timeliness. They will also act as a technical partner to product and program leadership, translating product vision into actionable technical direction.
The Data Engineer will design, build, and optimize ETL/ELT workflows and develop scalable data pipelines. They will also collaborate with cross-functional teams to deliver impactful data solutions.
The role involves bridging the gap between backend web development and data science teams, as well as developing backend data pipelines and integrating web services with databases. Additionally, the candidate will work on cutting-edge data processing infrastructure.
The MLOps Field Engineer will design and implement cloud infrastructure solutions for customers, focusing on AI/ML technologies. They will also work hands-on with technologies, deploying and testing solutions before handing them over to support teams.
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The Senior Data Engineer will design, build, and maintain the infrastructure for analyzing large data sets while collaborating with data scientists and stakeholders. They will also monitor and optimize the data infrastructure's performance and reliability.
The Regional Sales Manager will identify, develop, and execute a comprehensive account strategy to close new business and drive expansion growth. They will also maintain accurate sales forecasts and report on sales activity to senior management.
As a Senior Data Engineer, you will ensure the stability, scalability, and performance of the Data Science Framework (DSF) while working on big data processing components. You will analyze workload patterns and drive performance improvements, ensuring reliable and efficient Spark jobs.
Handle impactful customer technical projects, including designing reference architectures and productionalizing customer use cases. Collaborate with various teams to ensure technical components of engagements meet customer needs.
The R&D Data Elaboration Head is responsible for leading the digital transformation of R&D through data elaboration and visualization. This role involves overseeing the lifecycle of data models, developing analytical models, and fostering a culture of innovation within the team.
The Data Engineer will work across the full lifecycle of data engineering, including building and maintaining data pipelines and deploying solutions in production. They will also be responsible for fixing bugs, improving existing systems, and contributing to backend services.
The Business Data Analyst will focus on data analysis for business and product-related teams, providing insights that drive business growth. Responsibilities include conducting deep-dive analyses and creating actionable recommendations based on complex data analysis.
Collaborate with researchers and engineers to design and develop large language models and generative models for various applications. Implement, train, and fine-tune models on large-scale datasets to ensure optimal performance and accuracy.
Form successful relationships with clients to provide technical and business value. Support customers by authoring reference architectures and developing customized solutions.
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Design, develop and deploy scalable web applications and services. Drive architecture discussions and take ownership of new projects to deliver high-quality software.
Onboard eCommerce brands to AppLovin’s platform and educate them on growth solutions. Build strong relationships with key stakeholders to optimize campaigns and drive business outcomes.
The data scientist will define problems for ad delivery optimization and design KPIs/metrics, while also engaging in data preprocessing, modeling, and online deployment. They will collaborate with internal stakeholders to support decision-making and ensure continuous improvement of ad serving algorithms.
The Director, Advanced Analytics & AI is responsible for spearheading the strategy, development, and application of advanced analytics, machine learning, and artificial intelligence to optimize commercial operations. This role will oversee the deployment of advanced analytics driven tools, predictive analytics, and data science methodologies to drive revenue growth and enhance business decision-making.
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