Hadoop Jobs in Mexico.
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Sr. Solutions Engineer
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About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
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Role Description
We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.
Responsibilities
- Develop a deep understanding of customer journey phases and key business metrics
- Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
- Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
- Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes
- Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends.
- Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets
- Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
- Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
- Understand what matters most and prioritize ruthlessly
- Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate
Requirements
- Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
- 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
- Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
- Significant experience with SQL and large unstructured datasets such as Hadoop
- Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
- Solid background in running multivariate experiments to optimize a product or revenue flow
- Strong verbal and written communication skills
- Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus
Preferred Qualifications
- Product analytics experience in a SAAS company
- Masters’ or above in a quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
Compensation
Ready to apply?
Apply to Dropbox
Role Description
We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.
Responsibilities
- Develop a deep understanding of customer journey phases and key business metrics
- Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
- Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
- Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes
- Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends.
- Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets
- Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
- Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
- Understand what matters most and prioritize ruthlessly
- Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate
Requirements
- Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
- 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
- Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
- Significant experience with SQL and large unstructured datasets such as Hadoop
- Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
- Solid background in running multivariate experiments to optimize a product or revenue flow
- Strong verbal and written communication skills
- Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus
Preferred Qualifications
- Product analytics experience in a SAAS company
- Masters’ or above in a quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
Compensation
US Zone 1
This role is not available in Zone 1
Ready to apply?
Apply to Dropbox
Role Description
We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.
Responsibilities
- Develop a deep understanding of customer journey phases and key business metrics
- Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
- Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
- Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes
- Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends.
- Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets
- Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
- Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
- Understand what matters most and prioritize ruthlessly
- Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate
Requirements
- Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
- 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
- Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
- Significant experience with SQL and large unstructured datasets such as Hadoop
- Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
- Solid background in running multivariate experiments to optimize a product or revenue flow
- Strong verbal and written communication skills
- Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus
Preferred Qualifications
- Product analytics experience in a SAAS company
- Masters’ or above in a quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
Compensation
Ready to apply?
Apply to Dropbox
Caylent is a cloud native services company that helps organizations bring the best out of their people and technology using Amazon Web Services (AWS). We provide a full-range of AWS services including workload migrations and modernization, cloud native application development, DevOps, data engineering, security and compliance, and everything in between.
At Caylent, our people always come first. We are a global company and operate fully remote with employees in Canada, the United States, and Latin America. We celebrate the culture of each of our team members and foster a community of technological curiosity. Come talk to us to learn more about what it means to be a Caylien!
The Mission
We are seeking an Engineering Manager for our Cloud Data Engineering Practice. The right candidate is someone who is technically strong, can manage a team of Architects and Engineers, oversee data delivery engagements and is passionate about working with our customers, partners and employees to drive the business forward.
Your Assignment
- Manage a team of 5 - 8 cloud engineers and architects
- Interface with clients and internal teams to propose technical improvements using your cloud and engineering knowledge
- Take on hands-on technical responsibilities, including technical tasks in sprints
- Lead technical discussions with customers
- Handle code reviews and pull request management
- Manage task assignments within sprints
- Perform technical leadership activities like roadmap and vision checks, best practices implementation, and risk identification
- In-project mentoring (understand people on project & creation of growth opportunities) and sharing feedback for team members on the project
- Technical accountability on the delivery
- Kickoff new client engagements and act as a point of technical escalation
- Develop and review proposals and contracts and present these to clients
- Perform technical interviews for Architect and Engineer candidates
- Perform weekly 1:1s with your direct reports and guide their career development
Your Qualifications
- Strong experience in AWS data landscape
- Expertise in at least two major areas of Cloud Data Engineering:
- Relational database design, optimization and migration
- Big data processing using Spark, Hadoop, EMR etc
- Machine Learning and MLOps
- Advanced analytics using time series forecasting, descriptive and inferential statistics
- BI dashboards and visualizations
- Data Governance and MDM
- Experience with most of these:
- Infrastructure as Code tools
- CI/CD pipelines
- Application modernization and migration with a strong focus on databases
- Excellent written and verbal communication skills
Benefits
- 100% remote work
- Medical Insurance for you and eligible dependents
- Generous holidays and flexible PTO
- Competitive phantom equity
- Paid for exams and certifications
- Peer bonus awards
- State of the art laptop and tools
- Equipment & Office Stipend
- Individual professional development plan
- Annual stipend for Learning and Development
- Work with an amazing worldwide team and in an incredible corporate culture
Caylent is a place where everyone belongs. We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.
We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at hr@caylent.com.
NOTE: We’re unable to provide visa sponsorship now or at any time in the future.
At Caylent, we are committed to fair, transparent, and inclusive hiring practices. As part of our recruitment process, we may use artificial intelligence (AI) tools or automated systems to assist with the screening and evaluation of applications to help match candidate qualifications with job requirements.
These tools are designed to support — not replace — human decision-making. Final hiring decisions are always made by our trained recruitment professionals.
If an AI or automated tool is used during your application process, it will only be in accordance with applicable laws and regulations, and your information will be handled in a secure and confidential manner.
If you have any questions, please contact talent@caylent.com
Caylent is a place where everyone belongs. We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.
We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at hr@caylent.com.Ready to apply?
Apply to CaylentSenior Machine Learning Engineer - Not an Active Opening, Building Talent Pipeline
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Caylent is a cloud native services company that helps organizations bring the best out of their people and technology using Amazon Web Services (AWS). We provide a full-range of AWS services including workload migrations and modernization, cloud native application development, DevOps, data engineering, security and compliance, and everything in between.
At Caylent, our people always come first. We are a global company and operate fully remote with employees in Canada, the United States, and Latin America. We celebrate the culture of each of our team members and foster a community of technological curiosity. Come talk to us to learn more about what it means to be a Caylien!
Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits.
The Mission
At Caylent, a Senior Machine Learning Engineer works as an integral part of a cross-functional delivery team to design and document machine learning solutions on the AWS cloud for our customers. We are looking for someone that has a strong understanding of the various model types and tools, and can help our customers connect their business goals with the details of feature design, model training and inference. You will develop solutions designed by an architect.
You will participate in daily standup meetings with your team and bi-weekly agile ceremonies with the customer. Your manager will have a weekly 1:1 with you to help guide you in your career and make the most of your time at Caylent.
Your Assignments
- Work with a team to deliver machine learning solutions on AWS for customers
- Participate in and contribute to daily standup meetings
- Develop and implement ML models, MLOps, and analytics
- Big data processing and preparation of training data for models
Your Qualifications
- Strong experience in building ML models for real world applications
- Strong experience in at least one of these:
- AWS ML Services/SageMaker
- ML libraries like Keras, Tensorflow, PyTorch, Scikit-learn
- MLOps tools such as MLflow, Kubeflow, Airflow
- Advanced analytics using time series forecasting and/or inferential statistics
- Strong experience in one or more of these data processing solutions:
- Big data processing platforms like Spark, Hadoop, or streaming platforms
- Data processing and cleansing using Python/Pandas, PySpark, Scala, SQL
- Strong understanding of feature definition, model meta-data, hyperparameter tuning, stochastic gradient descent, deep learning layer types and activation functions
- Experience in visualization using SageMaker, ggplot, matplotlib, or seaborn
- Experience with an IaC tool such as CloudFormation, Amazon CDK or Terraform
- Excellent written and verbal communication skills
Benefits
- 100% remote work
- Medical Insurance for you and eligible dependents
- Generous holidays and flexible PTO
- Competitive phantom equity
- Paid for exams and certifications
- Peer bonus awards
- State of the art laptop and tools
- Equipment & Office Stipend
- Individual professional development plan
- Annual stipend for Learning and Development
- Work with an amazing worldwide team and in an incredible corporate culture
This role may require up to 25% travel, depending on business needs.
NOTE: We’re unable to provide visa sponsorship now or at any time in the future.
At Caylent, we are committed to fair, transparent, and inclusive hiring practices. As part of our recruitment process, we may use artificial intelligence (AI) tools or automated systems to assist with the screening and evaluation of applications to help match candidate qualifications with job requirements.
These tools are designed to support — not replace — human decision-making. Final hiring decisions are always made by our trained recruitment professionals.
If an AI or automated tool is used during your application process, it will only be in accordance with applicable laws and regulations, and your information will be handled in a secure and confidential manner.
If you have any questions, please contact talent@caylent.com
Caylent is a place where everyone belongs. We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.
We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at hr@caylent.com.Ready to apply?
Apply to CaylentEPAM NEORIS es un acelerador Digital que ayuda a las compañías a entrar en el futuro, teniendo 20 años de experiencia como Socios Digitales de algunas de las mayores compañías del mundo. Somos más de 4,000 profesionales en 11 países, con nuestra cultura multicultural de startup en donde cultivamos innovación, aprendizaje continuo para crear soluciones de alto valor para nuestros clientes.
Estamos en búsqueda de Desarrollador LRBA
Requerimientos:
- Esquema de trabajo híbrido en la CDMX Polanco/Reforma.
- Ing. tecnologías o similares (Titulado)
- Experiencia en el sector financiero (Altamente deseable)
- 2+ de experiencia en adelante.
Principales requerimientos técnicos:
- Java 8 en Adelante
- Spring Boot, Spring Batch, Spring Data
- SCRUM
- Maven
- Restful
- GITHUB
- Postman
- Sonar
- Hadoop
- Spark
- BitBucket
Ofrecemos:
- Esquema 100% nominal
- Prestaciones de Ley
- Vales de despensa
- Beneficios adicionales
- Plan de Desarrollo Profesional
- Colaboración multicultural
Te invitamos a conocernos en http://www.neoris.com, Facebook, LinkedIn, Twitter o Instagram: @NEORIS.
Oscar Alberto Lazcano Sánchez
(#LI-OL1)
Ready to apply?
Apply to NEORIS