20 publicaciones de empleo destacadas de data scientist , amazon music en dif (¡Están contratando!)

Cloud Data Analytics Engineer New
Dotmatics —Ciudad de México, CDMX
- Microsoft Powerpoint
- Microsoft Excel
- Administración de personal
1d
Machine Learning Engineer - Fraud
PayJoy —Ciudad de México, CDMX
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Zillow.com —Ciudad de México, CDMX
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IQVIA —Ciudad de México, CDMX
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Salesforce —Ciudad de México, CDMX
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Constellation Brands —Ciudad de México, CDMX
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Zendesk —Ciudad de México, CDMX
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Ucloud —Ciudad de México, CDMX
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Cloud Data Analytics Engineer New

Dotmatics -
Ciudad de México, CDMX

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Información del empleo

Hace 1 día

Cualificaciones

Microsoft Powerpoint
Gestión de costos
Looker
Microsoft Excel
Administración de personal
Tooling
AWS Certification
Análisis de datos
Git
Inglés
Google Cloud Platform
Tableau
Experiencia en bases de datos
SQL
Sistemas de control de versiones
Liderazgo
Python

Descripción completa del empleo

Our Why At Dotmatics

At Dotmatics, a Siemens company, we believe science, data, and decision-making must be deeply intertwined for innovation to thrive. Our Portfolio includes Luma, LumaLab Connect, ELN Platform, Graphpad Prism, Geneious, SnapGene, Protein Metrics, OMIQ, FCS Express, LabArchives, NQuery, EasyPanel, SoftGenetics and Virscidian.

We have a vision for a new Lab of the Future that will change the future of scientific research.

We have created the world’s most comprehensive digital science platform – best-of-breed software applications already used by more than 2 million scientists, together in a single ecosystem united by a powerful, flexible enterprise data platform. This is not flat data buried away in digital graveyards. This is dynamic, multi-dimensional decision-making.

Scientific enterprises need a new level of effectiveness to achieve tomorrow’s breakthroughs. Illness will not wait. The biosphere will not wait. We are tireless in our vision, because the time for innovation is now.

Shaping the Future of Science At Dotmatics

Our global team of more than 800 colleagues are dedicated to supporting our customers in over 180 countries. Together, with our scientific community of users, we accelerate scientific innovation in order to make the world a healthier, cleaner, and safer place to live.

You’ll join a collaborative, global team pushing the boundaries of scientific innovation. Your ideas and efforts will have a tangible impact, accelerating scientific progress and discovery. We offer a dynamic, remote-friendly environment that fosters high integrity and collaboration, empowering you to excel. Dotmatics is a company built by scientists, for scientists. Combined, we are now the world’s largest cloud-based scientific research R&D platform. We need your help to keep growing and pioneering the future.

We are Science Driven. We are Customer Centric. We are Better Together.

What do we need

Dotmatics is seeking a Data Analytics Engineer to support the Luma team, you will own the operational health, architecture intelligence, and cost optimization of our cloud environments, AI usage customer data and more. In this role you will develop a deep understanding of our infrastructure, connect architectural decisions to business outcomes, and give the engineering leadership, Senior leadership and Corporate Data teams the visibility they need to make smart, cost-conscious decisions at scale.

In this role you will get to:

Cloud Data Architecture and Cost Intelligence

Develop and maintain a comprehensive technical understanding of the organization’s cloud architecture across all major infrastructure components.
Map the relationship between architectural decisions and cost drivers, producing clear models that connect system behaviour to spend.
Identify cost anomalies, inefficiencies, and optimization opportunities across compute, storage, networking, and managed services.
Build and maintain dashboards and reporting that give engineering and leadership real-time visibility into cloud cost trends.
Develop high-impact reporting and analytics providing visibility into engineering and customer operations, lead efforts to scale reporting through automation
Partner with internal stakeholders (Sales, Product, Marketing, Finance, etc.) to increase the understanding, visibility and use of business metrics, encourage self-service analytics
Perform ad hoc data exploration and analysis to answer immediate business needs.
Identify opportunities to improve data quality, performance, and observability
Help develop standards for analytics engineering best practices

Technical Operations

Help define and enforce cloud governance policies including tagging standards, resource lifecycle management, and rightsizing practices.
Partner with engineering teams to review architectural decisions for cost impact before and after deployment.
Maintain runbooks and documentation for operational data management processes.

Stakeholder Collaboration

Serve as the primary point of contact for cloud cost and operations questions from engineering, finance, and executive stakeholders.
Translate complex technical findings into clear, business-oriented recommendations for non-technical audiences.
Collaborate with engineering leadership on roadmap decisions that have infrastructure and cost implications.
Work cross-functionally on handoffs and alignment across shared operational responsibilities.

We are looking for people who have 5+ years of experience in data analysis with a deep understanding of cloud operations, cloud architecture, or a related technical infrastructure role, with demonstrated experience analysing and optimising cloud spend at enterprise scale. This role requires advanced proficiency in English, including the ability to communicate complex ideas clearly in writing and speech, given the level of client interaction and cross-functional leadership involved.

The key skills we are looking for are:

Advanced SQL and/or Python, particularly data science and report generation frameworks.
Hands-on experience with AWS or Databricks, with a strong preference for multi-cloud expertise.
Strong understanding of cloud-native architectures including containerisation, serverless, managed databases, and distributed systems.
Experience with observability and monitoring platforms such as Datadog, CloudWatch, or equivalent.
Ability to produce clear written and visual communication of technical findings for executive audiences.
Familiarity with version control systems (e.g., Git) and CI/CD workflows for data engineering projects
BI tools (e.g., Looker, Mode, Tableau)
Ability to work directly with business teams to align on KPIs, define requirements, and deliver impactful insights
Comfortable writing and maintaining data dictionaries, dbt Docs, or internal wikis
Ability to design and build BI assets that are explainable and sustainable whether they are excel spreadsheets, BI dashboards or powerpoint presentation.

You may also have:

Experience in life sciences, pharma, or regulated industry cloud environments including GxP or 21 CFR Part 11 contexts.
Familiarity with FinOps frameworks and cloud cost management tooling such as CloudHealth, Apptio, or native cloud cost tools.
Prior experience in a high-growth SaaS or enterprise software company.
Relevant certifications such as AWS Solutions Architect, GCP Professional Cloud Architect, or FinOps Certified Practitioner.

Research shows us the confidence gap and imposter syndrome can get in the way of meeting outstanding candidates, so please don’t hesitate to apply — we’d love to hear from you.

By submitting your application, you agree that Dotmatics may collect your personal data for recruiting, global organization planning, and related purposes. Dotmatics Privacy Notice explains what personal information we may process, where we may process your personal information, our purposes for processing your personal information, and the rights you can exercise over Dotmatics use of your personal information.

Dotmatics is an equal opportunity employer. We are a welcoming place for everyone, and we do our best to make sure all people feel supported and connected at work.

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data scientist , amazon music empleos en dif

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