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Data Engineer

Data Engineer II, DASH Device Operations

Amazon

Mexico City

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Описание вакансии

Description
We are seeking a talented, self-directed Data Engineer to design, build, and operate large-scale, high-performance data infrastructure that powers analytics, AI/ML workloads, and intelligent automation across Device Operations. You will implement data structures using best practices in data modeling and ETL/ELT processes, build real-time and batch pipelines, and enable AI-ready data foundations that support both traditional BI and emerging agentic systems. You will gather business and functional requirements and translate them into robust, scalable solutions that work within the broader data architecture. You will analyze source systems, drive best practices with partner teams, and participate in the full development lifecycle — from design and implementation to documentation, delivery, and operational support.

The ideal candidate relishes working with large volumes of data, enjoys the challenge of highly complex technical contexts, and is passionate about enabling data-driven decisions at scale. They are an expert in data modeling, ETL design, and data warehousing — and are energized by the intersection of data engineering and AI/ML, where well-structured data infrastructure creates an outsized impact on intelligent systems. They are a self-starter, comfortable with ambiguity, able to think big while paying careful attention to detail, and thrive in a fast-paced, collaborative environment.

Key job responsibilities

Design, implement, and operate scalable data pipelines (batch and real-time) that serve analytics, reporting, and AI/ML workloads

Build and maintain data infrastructure that supports AI-ready datasets — structured for consumption by machine learning models, agents, and natural language interfaces

Interface with technology teams to extract, transform, and load data from diverse sources using SQL, Python, and distributed computing frameworks

Implement data models and ETL/ELT processes using best practices in dimensional modeling, data vault, or hybrid approaches on MPP data warehouses

Build robust data integration pipelines using SQL, Python, and Spark across batch and streaming paradigms

Design and deliver high-quality datasets that support business analysis, customer reporting, and AI/ML feature engineering

Partner with scientists and application engineers to ensure data infrastructure meets the needs of ML training, inference, and agentic automation systems

Interface with business customers, gather requirements, and deliver complete, well-documented data solutions

Evaluate and make decisions around dataset designs, pipeline architectures, and tooling proposed by peer engineers

Produce comprehensive dataset documentation, metadata, and data lineage artifacts

Mentor junior data engineers on best practices in data engineering, code quality, and operational excellence

A day in the life

You will work across the full spectrum of data engineering — building pipelines that ingest from operational systems, designing warehouse schemas that serve thousands of daily queries, optimizing infrastructure for cost and performance, and enabling new AI/ML capabilities by making data accessible, reliable, and well-governed. You will collaborate with scientists, BI engineers, and application developers to solve problems that span traditional analytics and emerging intelligent systems. Some days you will be deep in SQL optimization; other days you will be designing real-time CDC pipelines or enabling a new agent to query data programmatically.

About The Team
The Data, Analytics, and Science Hub (DASH) team builds scalable data platforms, analytical frameworks, AI-powered solutions, and reporting infrastructure to support Device Operations & Supply Chain. DASH serves multiple organizations across DeviceOps — delivering data engineering, business intelligence, and science capabilities that power operational decision-making. The team operates at the intersection of data infrastructure and AI innovation, building systems that serve both human analysts and intelligent agents supporting Device Ops users.

Basic Qualifications

  • Bachelor's degree in a quantitative/technical field such as computer science, engineering, statistics
  • 4+ years of data engineering, database engineering, business intelligence or business analytics experience
  • Experience in writing complex, highly-optimized SQL queries across large datasets
  • 4+ years of development/programming/scripting language (Python/Java/Bash/Perl) experience
  • Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
  • Experience in Redshift, or experience in Hive/Spark/Hbase/Yarn and experience in Kafka
  • Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
  • Knowledge of distributed systems as it pertains to data storage and computing

Preferred Qualifications

  • Master's degree in engineering, statistics, computer science, mathematics, or a related quantitative field
  • Experience with data infrastructures: relational analytic DBMS, Elastic-Search, and Big Data EMR/EC2/Glue/Lambda, or experience with training and deploying machine learning systems to solve large-scale optimizations
  • Experience with infrastructure as code, ops automation, and configuration management tools such as Chef, Puppet, or Ansible
  • Experience communicating with users, other technical teams, and management to collect requirements, describe data modeling decisions and data engineering strategy
  • Experience as a mentor, tech lead or leading an engineering team, or experience debugging, profiling, and implementing best software engineering practices in large-scale systems
  • Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how\-we\-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Company
- Servicios Comerciales Amazon Mexico S. de R.L. de C.V.

Job ID: A10449141

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Data Engineer

Acceleration Center - Data Engineer - Manager

PwC México

Mexico City

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Описание вакансии

The Opportunity

Join our Acceleration Center Mexico and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As an Acceleration Center - Data Engineer - Manager, you will focus on utilizing advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. Within our Tax practice, you will leverage skills in data manipulation, visualization, and statistical modeling to support clients in solving complex business problems. As a Manager, you will lead teams, focusing on strategic planning and mentoring junior staff. You are accountable for the execution of project success and maintaining standards. Enhancing your leadership style, you motivate, develop, and inspire others to deliver quality. You are responsible for coaching, leveraging team members' unique strengths, and managing performance to deliver on expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.

In this role at PwC Acceleration Center Mexico, you will take ownership of projects, validating their successful planning, budgeting, execution, and completion. You will work with team leadership to establish collective ownership of quality, timelines, and deliverables. This is an opportunity to develop skills outside your comfort zone and encourage others to do the same.

Responsibilities

  • Leading data analysis workstreams to drive insights and support strategic decision-making
  • Utilizing advanced analytics techniques to extract meaningful insights from large datasets
  • Developing and implementing data-driven solutions to optimize client operations
  • Managing and mentoring teams to enhance performance and deliver quality outcomes
  • Building and maintaining data pipelines and integration processes for seamless data flow
  • Designing and deploying data visualization tools to communicate complex data insights
  • Conducting exploratory data analysis to identify trends and opportunities for improvement
  • Collaborating with stakeholders to address data challenges and align on project goals
  • Confirming data integrity and security within analytics frameworks
  • Leveraging tools like Alteryx, Power BI, and Tableau to enhance data analysis capabilities
  • Applying statistical modeling and predictive analytics to solve complex business problems
  • Encouraging innovation and embracing technology to improve data analysis processes

What You Must Have

  • At least a High School Diploma or the equivalent degree
  • At least 4 years of experience
  • Oral and written proficiency in English required

What Sets You Apart

  • Preference for at least one of the following fields of study: Accounting, Engineering, Data Processing/Analytics/Science, Computer and Information Science, Economics, Finance
  • At least one of the following: A Certification in databases (Databricks, MS SQL), visualization tools (Power BI), cloud platforms (AWS, Azure, GCP), or predictive modeling/ML (Python, SAS)
  • Demonstrating proficiency in data analysis and data modeling
  • Utilizing advanced skills in data visualization tools like Tableau
  • Excelling in complex data analysis and data-driven insights
  • Managing data pipelines and data integration processes
  • Leading teams in developing data quality improvement plans

Это сохранённая копия объявления, опубликованного в другом месте. Вакансии снимают без предупреждения — перед откликом проверьте сайт работодателя. mentors.coach не является нанимающей стороной.

Data Engineer

PMTS - Principal Agentic Data Engineer

Salesforce

Mexico Citylead

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Описание вакансии

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category

Software Engineering

Job Details

About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

Principal Agentic Data Systems Engineer
Mexico City | Hybrid

Department Overview
The Enterprise Data & AI Solutions group is the organization’s strategic hub for cognitive automation. We move beyond traditional data management to build the autonomous engines that power executive decision-making. Our team is composed of Architects of Autonomy—professionals with the technical depth to build systems from the ground up and the strategic vision to leverage AI to ensure scalability. We partner with the C-suite to solve high-complexity challenges by deploying sophisticated multi-agent ecosystems that operate with continuous uptime.
Role Description: From Execution to Orchestration
We are seeking a Principal Agentic Data Systems Engineer. This is a role for a technical visionary who has mastered traditional data engineering and is now focused on the next frontier: Agentic Force Multiplication.
You are someone who knows how to supercharge their workflows.
In this position, you shift from being a traditional individual contributor to a Human-in-the-Loop (HITL) Orchestrator. You will serve as the primary architect of a high-performing digital workforce, operating as a "Team of One" that achieves the output equivalent of a 3-5 person engineering squad. Your value lies not in manual coding, but in the high-level design and supervision of autonomous agents that execute engineering, QA, governance, and analytics workflows on your behalf.
The Strategic Shift: You are redefining the data team model. Instead of managing human personnel, you manage complex "hand-off" protocols between specialized AI agents, acting as the central anchor for a hybrid human-agent intelligence unit.
Core Responsibilities

  • Autonomous Scaling: Architect and maintain a private ecosystem of 10+ autonomous agents specialized in ETL, synthetic data generation, automated QA, and predictive modeling.
  • Agentic Orchestration: Design multi-step reasoning architectures and verification protocols to ensure agents autonomously validate and peer-review their own outputs.
  • Complex Problem Resolution: Transform high-level, ambiguous business requirements into production-ready data products independently, bypassing the need for mid-level project management.
  • Governance & Oversight: Use domain knowledge to ensure deployed tools are well governed. Governance as code for data pipelines and Agentic development. Context aware Agent development.
  • Contextual Integration: Develop and maintain Model Context Protocol (MCP) servers to provide agents with secure, deep-link access to Snowflake, Salesforce, AWS, and proprietary internal data catalogs.

Technical Profile

  • Engineering Foundation: Production-grade proficiency in Python, dbt, Airflow, and advanced SQL. Apache Spark, and Snowflake.
  • AI Orchestration: Fluency in AI-native development environments (e.g., Cursor, Codex, or Claude Code). Expert in Prompt Engineering. Mastery of agentic frameworks such as LangGraph. Leverage MCP servers to retrieve data from tool stack
  • Cognitive Architecture: Expert-level knowledge of chain-of-thought prompting, self-correction loops, and iterative reasoning paths.
  • Salesforce Knowledge: Salesforce Core and Data 360 understanding
  • Systems Design: Advanced understanding of Data Mesh, Data-as-a-Product (DaaP), and Event-Driven Architectures. Semantic layer. Knowledge Graphs.
  • Cloud Infrastructure: Experience using agentic workloads via Docker, Kubernetes, and serverless compute environments.

Qualifications

  • Experience: 7+ years of experience in high-stakes Data Engineering, Architecture, or Data Science.
  • Senior experience with Python & SQL
  • Operational Leverage: A documented history of using generative AI to accelerate personal and departmental output by orders of magnitude.
  • Strategic Autonomy: The ability to function as a "Domain Data Officer," managing end-to-end data strategy for a business unit with minimal supervision.
  • Technical Intuition: Superior analytical judgment—the ability to identify subtle logic errors or hallucinations in agentic output before they reach production.

A Day in the Life: Operational Workflow
08:00 – Intelligence Synthesis
While you start your day, your "Scout Agents" have already completed an automated audit of the overnight data pipelines. You review a synthesized report highlighting three anomalies in the global revenue stream. One agent has already drafted a proposed SQL remediation and a unit test; you review the logic and authorize the deployment to production.
Stakeholder triage and problem framing/overnight pipeline audit, anomalies, drafted SQL remediation, unit test, approve deployment:

  • Claude Code / Claude Enterprise / Codex / Agentforce-style command layer
  • Snowflake, Tableau metadata, dbt artifacts, pricing event logs
  • ranked brief with pricing overrides, lineage breaks, semantic definitions, supporting evidence
  • human deciding noise vs escalation vs today’s work

10:30 – Architectural Orchestration
A request arrives from the CFO for a "High-Resolution Market Volatility Stress Test." Rather than building the model manually, you define the parameters for your agentic fleet. You orchestrate a "Research Agent" to pull external market indicators, a "Simulation Agent" to run the Monte Carlo iterations, and a "Synthesis Agent" to build a live-updating executive dashboard. You spend your time on validation and strategic interpretation.
13:30 – Knowledge Retrieval & Documentation
You encounter a legacy pricing algorithm with no surviving documentation. You deploy an "Information Retrieval Agent" to parse thousands of historical Slack threads, Jira tickets, and GitHub commits. Within minutes, the agent provides a technical summary of the original design intent. You direct the agent to update the global metadata repository so this knowledge is permanently accessible to the organization.
legacy algorithm overview/chage, retrieval across historical Slack / Jira / GitHub, technical summary, metadata repository update.

  • leadership-triggered critical investigation
  • search across SQL corpus, dbt lineage, notebook agents
  • drafted explanations and SQL patches
  • converting findings into a leadership action plan

15:30 – Defensive Systems Engineering
You dedicate time to "Security & Integrity Engineering," building new "Red-Team Agents" whose sole purpose is to attempt to find flaws in the logic or security vulnerabilities in your other agents. You are building a self-healing digital immune system for the company's data.
Agents prepare modeling and simulation workflows to test strategic scenarios such as pricing or renewal changes. The human selects methods, reviews assumptions, and interprets uncertainty before any decision is actioned.
18:00 – Asynchronous Task Deployment
You initialize a long-tail analytical task: "Analyze the last 24 months of customer churn data and identify latent correlations that current linear models have missed." You disconnect while the agentic fleet begins the heavy compute and reasoning cycles overnight.
*20:00+ – Long-Tail Agent Execution

After hours, agents continue computationally heavy or long-horizon tasks, creating a curated queue of opportunities, risks, and partially completed work for the next morning.*
Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and
be your best
, and our AI agents accelerate your impact so you can
do your best
. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

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Data Engineer

Acceleration Center - Data Engineer - Associate

PwC México

Mexico City

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Описание вакансии

The Opportunity

Join our Acceleration Center Mexico and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As an Acceleration Center - Data Engineer - Associate, you will focus on utilizing advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. Within our Tax practice, you will leverage skills in data manipulation, visualization, and statistical modeling to support clients in solving complex business problems. As an Associate, you will be driven by curiosity, contributing to projects while developing your skills and knowledge to deliver quality work. You will engage in research, participate in project tasks, and develop basic skills and knowledge, all while building a personal brand and understanding the broader objectives of your role.

In this role at PwC Acceleration Center Mexico, you will adapt to working with a variety of clients and team members, each presenting unique challenges and scope. You will take ownership and consistently deliver work that drives value for our clients and success as a team. Embrace the opportunity to learn and grow, as every experience is a chance to enhance your skills and build meaningful connections.

Responsibilities

  • Leveraging advanced analytics techniques to extract insights from large datasets and drive data-driven decision-making
  • Utilizing data manipulation, visualization, and statistical modeling to support clients in solving complex business problems
  • Developing and maintaining data pipelines and data warehouses to validate data integrity and accessibility
  • Conducting exploratory data analysis to identify trends and patterns that inform strategic decisions
  • Building dashboards and reports using tools like Power BI and Tableau to visualize data insights effectively
  • Applying algorithm development and predictive modeling to enhance business data analytics capabilities
  • Collaborating with team members and clients to gather information and analyze facts for informed decision-making
  • Implementing data quality improvement plans to enhance data accuracy and reliability
  • Engaging in research and analysis to support customer needs and optimize operations
  • Adapting to diverse perspectives and challenges in a fast-paced environment to deliver quality work consistently

What You Must Have

  • Bachelor degree
  • Oral and written proficiency in English required

What Sets You Apart

  • Preference for at least one of the following fields of study: Accounting, Engineering, Data Processing/Analytics/Science, Computer and Information Science, Economics, Finance
  • At least one of the following: A Certification in databases (Databricks, MS SQL), visualization tools (Power BI), cloud platforms (AWS, Azure, GCP), or predictive modeling/ML (Python, SAS)
  • Demonstrating proficiency in data analysis and visualization tools
  • Utilizing Python for data manipulation and predictive modeling
  • Engaging in exploratory data analysis to uncover insights
  • Applying machine learning techniques to solve complex problems
  • Developing dashboards and reports using Power BI and Tableau

Это сохранённая копия объявления, опубликованного в другом месте. Вакансии снимают без предупреждения — перед откликом проверьте сайт работодателя. mentors.coach не является нанимающей стороной.

Data Engineer

Desarrollador/a de Datos (Ciudad de México, Miguel Hidalgo)

BBVA en México

Mexico City

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Описание вакансии

Fecha límite para apuntarse:
2026-08-16

¿Quieres desarrollar tu carrera profesional?
BBVA es una empresa global con más de 160 años de historia que opera en más de 25 países en los que damos servicio a más de 80 millones de clientes. Somos más de 121.000 profesionales que trabajamos en equipos multidisciplinares y de perfiles tan diversos como financieros, expertos jurídicos, científicos de datos, desarrolladores, ingenieros o diseñadores.

¿Qué estamos buscando?
¿Qué estamos buscando?
Buscamos un profesional en desarrollo de datos orientado a la innovación y el trabajo colaborativo, con capacidad para diseñar soluciones de Big Data eficientes y escalables. Este rol impulsará la automatización, la integración de datos y la mejora continua de los procesos internos. Formarás parte de un equipo enfocado en potenciar las capacidades tecnológicas y de inteligencia artificial de la institución, asegurando la escalabilidad y calidad de las soluciones implementadas en la nube.

Principales Responsabilidades

  • Diseñarás y desarrollarás soluciones de integración y Big Data, incluyendo aprovisionamientos, ingestas, persistencias y procesos de QA.
  • Ejecutarás proyectos bajo metodologías Agile, implementando procesos exhaustivos de prueba y validación con las herramientas y directrices definidas.
  • Coordinarás el despliegue de soluciones de datos en entornos de producción bajo estándares de Gobierno, Calidad y gestión de cambios.
  • Garantizarás que las soluciones de datos estén diseñadas para escalarse y operar eficientemente a medida que crezcan los volúmenes de datos en entornos de nube.
  • Propondrás ideas innovadoras para la mejora de procesos y la optimización continua de los desarrollos dentro del área.

Retos del Puesto
Asegurar que las soluciones de datos y Big Data estén diseñadas para escalarse y funcionar de manera eficiente a medida que crecen los volúmenes de información en la nube, alineándose a las herramientas Next Gen de Arquitectura y a los protocolos de Gobierno y Calidad.

Requisitos
Conocimientos y Experiencia

  • Conocimientos Obligatorios: Kirby, AWS, Control-M, conocimientos en tecnología de IA.
  • Conocimientos Deseables: Data X y conocimientos en Datum.
  • Escolaridad: Ing. en sistemas, computación o afin
  • Experiencia: 1 a 2 años de experiencia en el desarrollo de datos.

Competencias Clave

  • Aprendizaje continuo
  • Pensamos en grande
  • Toma de decisiones

¿Cómo postularte?
Si te encuentras interesado/a, postúlate dando clic en ‘Solicitar’.

En caso de requerir algún ajuste razonable(1) en tu proceso de selección, comunícalo al reclutador/a en el primer contacto.

En BBVA creemos que contar con un equipo diverso, nos hace ser un mejor banco. Por este motivo apoyamos activamente la diversidad, la inclusión y la igualdad de oportunidades, sin importar cual sea su origen étnico o nacional, sexo, edad, religión, discapacidad, orientación sexual, identidad o expresión de género, la condición social, la condición de salud, las opiniones, el estado civil o cualquier otra que atente contra la dignidad humana y tenga por objeto anular o menoscabar los derechos y libertades de las personas. Estamos seguros que cultivando un ambiente de trabajo colaborativo e inclusivo podremos mostrar lo mejor de nosotros mismos.

  • Los ajustes razonables comprenden las modificaciones y/o adaptaciones que podrá hacer la empresa , durante tu proceso de selección, con la finalidad de que puedas llevar a cabo dicho proceso de forma adecuada.

BBVA: Transformando sueños en oportunidades ¿Listo(a) para crear juntos?

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Data Engineer II, DASH Device OperationsAmazon · Mexico

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