20 publicaciones de empleo destacadas en data engineer (databricks) (¡Están contratando!)

People Data & Insights Engineer
Takeda Pharmaceutical —Cuajimalpa, CDMX
- Tiempo completo
- Inglés
- SQL
- Licenciatura
Machine Learning Engineer
Capital Empresarial Horizonte —Benito Juárez, CDMX
- $50,000 a $85,000 por mes
- Tiempo completo
- Trabajo híbrido
- Azure
- Inglés
- Experiencia en bases de datos
Postulación rápida
3d
Lead Data Software Engineer (Python, AWS, Databricks)
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Inglés
- Python
- Plan de adquisición de acciones empresariales
Lead Data Software Engineer (Python, Azure, Databricks)
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- Inglés
- Python
- Plan de adquisición de acciones empresariales
Data Engineer Specialist (Queretaro)
PPG —Querétaro, Qro.
- Tiempo completo
- SQL
- Mejora continua
- Presencial
- Seguro de vida
Postulación rápida
Data Engineer - Azure
Accenture —Monterrey, N. L.
- Tiempo completo
- Azure
- Inglés
- SQL
Senior Analytics Engineer
Mastercard —Ciudad de México, CDMX
- Tiempo completo
- Experiencia en bases de datos
- SQL
- Python
MLOps Engineer
TERATIC —Guadalajara, Jal.
- $48,000 a $55,000 por mes
- Correo electrónico
- Trabajo híbrido
- Python
- Seguro dental
- Vacaciones adicionales o permisos con goce de sueldo
Postulación rápida
Engineering & Quality - Software Engineer
Fitch Group —Monterrey, N. L.
- Azure
- Python
- Permiso de maternidad y paternidad
Senior Data Software Engineer (Python & SQL)
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Inglés
- SQL
- Python
- Vacaciones adicionales o permisos con goce de sueldo
Senior AI Data Engineer
Scribd, Inc. —Ciudad de México, CDMX
- Tiempo completo
- CAD
- SQL
- Presencial
- Seguro dental
- Vacaciones adicionales o permisos con goce de sueldo
Ingeniero de Datos
PROGRAMMING.COM —Guadalajara, Jal.
- Tiempo completo
- Home Office (Desde casa)
- Azure
- SQL
- Disponible para viajar
Postulación rápida
6d
Sr Advanced AI Data Engineer
Honeywell —Monterrey, N. L.
- Tiempo completo
- Microsoft Excel
- Azure
- DevOps
Lead Azure Data Engineer
Infosys —Guadalajara, Jal.
- Azure
- Informática
- Inglés
Postulación rápida
11d
Data Engineering Academy (Snowflake - Databrick) 2748 -
Xideral —Monterrey, N. L.
- Tiempo completo
- Home Office (Desde casa)
- Inglés
- SQL
- Licenciatura
Postulación rápida
la26.042 - Data Engineering Lead
Tiger Analytics Inc. —Ciudad de México, CDMX
- Home Office (Desde casa)
- Azure
- DevOps
- Inglés
Postulación rápida
Consultor/a de datos en Azure
SDG Group —Ciudad de México, CDMX
- Azure
- Inglés
- SQL
Postulación rápida
Senior Data Platform Engineer
Nouryon —Ciudad de México, CDMX
- Tiempo completo
- Azure
- Administración de personal
- Informática
12d
Consultor Databricks Senior
NetPartners International —Ciudad de México, CDMX
- Español
- Azure
- DevOps
Postulación rápida
Software Development Specialist
NTT Ltd —Ciudad de México, CDMX
- Azure
- Administración de personal
- Informática
5d

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People Data & Insights Engineer

Takeda Pharmaceutical -
Cuajimalpa, CDMX

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Información del empleo

Tiempo completo

Cualificaciones

ATS
Inglés
SQL
Licenciatura
Recursos humanos
Python

Descripción completa del empleo

By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.

Job Description

We are seeking a People Data & Insights Engineer to build and scale the data foundation that powers People Analytics at Takeda. This role sits at the intersection of data engineering and workforce insights, focusing on transforming complex HR and employee experience data into structured and reliable data assets.

This position is embedded within Takeda’s People Analytics and Capabilities team and requires deep engagement with HR use cases such as talent metrics, employee listening, and workforce planning, ensuring data is not only technically sound, but analytically meaningful.

How you will contribute

Design and maintain robust pipelines that integrate HR systems (HRIS, ATS, survey/listening platforms, etc.) into curated, reusable datasets. Build data models that support consistent reporting, longitudinal analysis (e.g., workforce changes over time), and deeper insights into employee experience.
Partner closely with People Analysts and HR stakeholders to understand evolving business questions and embed them into well-designed data models and pipelines.
Implement validation checks, reconciliation logic, and monitoring processes to ensure the integrity of people data across sources and time.
Build and maintain datasets that power consistent reporting across core People Analytics domains (e.g., hiring, retention, mobility, skills, engagement).
Create clear documentation and reusable frameworks to improve how people data is modeled, accessed, and reused across the function.
Apply AI-assisted approaches (e.g., code generation, data exploration, documentation, and troubleshooting) to accelerate development, improve code quality, and streamline pipeline and data model creation.

Skills and qualifications

Bachelor’s degree in a quantitative field (e.g., Data Science, Computer Science, Economics, Analytics) or equivalent experience
~3–6 years of experience in analytics, data engineering, or people analytics
Advanced SQL and experience working with large, complex datasets
Proficiency in Python (or similar) for data processing and automation
Experience with cloud data platforms (e.g., Databricks, Snowflake)
Strong experience designing analytical data models (e.g., dimensional modeling, time-series structures)
Proficiency communicating in English language is mandatory
Experience working with HR data (HRIS, recruiting, survey/listening platforms) or other complex behavioral datasets
Ability to translate ambiguous business questions into structured data solutions
Strong attention to detail and commitment to data quality

Locations

MEX - Santa Fe

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time

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