Expert Data Scientist

Expert Data Scientist (Analytics Data)

Position Snapshot:

Type of Contract: Full Time

Function and Stream: NUSA

Type of work: Hybrid

Work Language: Fluent Business English

The role:

The Expert Data Scientist (Analytics Data) will be responsible for building, maintaining, and optimizing analytical data capabilities that enable scalable data ingestion, transformation, modeling, and access across analytics platforms such as Power BI, Snowflake, Databricks, and Azure. This role develops reusable data models, pipelines, frameworks, automation, and analytical platform patterns that ensure data is reliable, performant, secure, cost-effective, and aligned with enterprise standards for governance, security, quality, and interoperability.

The role will operate as an expert technical contributor, partnering closely with business, analytics, data product, engineering, architecture, security, platform, and regional/global IT stakeholders to strengthen the data foundation for BI, advanced analytics, AI/ML, and enterprise data products.

What you’ll do:

As an Expert Data Scientist (Analytics Data) you will:

Design, build, maintain, and optimize analytical data capabilities that support scalable data ingestion, processing, transformation, modeling, governance, and access across Power BI, Snowflake, Azure Datalake, Databricks, and related cloud data services.
Develop reusable analytical datasets, data pipelines, engineering frameworks, templates, automation scripts, and standard patterns that accelerate delivery while reducing operational friction, duplication, and technical risk.
Optimize Snowflake, Power BI, Databricks, Azure Synapse, and related analytical platform components for performance, reliability, scalability, cost efficiency, observability, and operational resilience.
Embed governance, security, quality, lineage, metadata, access controls, auditability, and compliance requirements into analytical data capabilities and data engineering patterns by design.
Partner with data engineers, analytics engineers, data product teams, architects, platform teams, and business stakeholders to translate business and analytics needs into scalable, reusable, and supportable data capabilities.
Troubleshoot complex data pipeline, analytical platform, integration, access, compute, storage, performance, and reliability issues; lead root-cause analysis and drive durable remediation.
Create documentation, reference implementations, standards, and enablement materials that improve developer productivity, self-service adoption, and consistent use of analytical data capabilities.
Stay current with modern analytical data platform practices, distributed systems, data observability, data contracts, metadata-driven automation, FinOps, MLOps enablement, and platform-as-product operating models.

We offer you:

We offer more than just a job. We put people first and inspire you to become the best version of yourself.

Great benefits including salary and a comprehensive social benefits package. We have one of the best pension plans on the market, as well as flexible remuneration with tax advantages: health insurance, restaurant card, mobility plan, etc.
Personal and professional growth through ongoing training and constant career opportunities reflecting our conviction that people are our most important asset.
Hybrid working environment with flexible working scheme. Our state-of-the-art campus is dog friendly and equipped with a medical center, canteen and areas to co-create network and chill!
Recreation activities such as yoga, Zumba, etc. and a wide range of volunteering activities.

Join our global team of IT professionals at Nestlé, driving daily innovation and leveraging cutting-edge technologies to address digital opportunities. Grow professionally in a dynamic and impactful environment, collaborating with business partners worldwide to deliver integrated technology solutions!

What will make you a great fit?

Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, Data Analytics, or a related field; equivalent experience will be considered.
8+ years of experience in data engineering, analytics engineering, data platform engineering, cloud data platforms, software engineering for data systems, or related technology roles.
Expertise building and optimizing scalable analytical data systems across platforms such as Snowflake, Power BI, Databricks, Microsoft Azure, Spark, SQL-based platforms, cloud storage, and cloud-native data services.
Advanced proficiency with SQL and modern programming languages such as Scala, Python, or Java, with strong software engineering practices for reusable, testable, and maintainable code.
Deep experience designing and operating analytical data platforms, data lakes, lakehouses, data warehouses, hybrid architectures, data pipelines, orchestration frameworks, and enterprise-scale ingestion and transformation patterns.
Strong hands-on experience with batch, streaming, and near-real-time data processing; ETL/ELT frameworks; structured, semi-structured, and unstructured data integration; and high-volume data movement patterns.
Experience with Snowflake capabilities such as warehouse optimization, secure data sharing, role-based access, performance tuning, storage and compute management, and governed data consumption patterns.
Strong knowledge of CI/CD, automation, monitoring, alerting, observability, incident response, root-cause analysis, environment management, and operational excellence practices.
Strong communication, problem-solving, documentation, stakeholder management, and cross-functional collaboration skills, with fluency in English.
Proactive and agile mindset, with the ability to work effectively as an expert technical contributor in a dynamic analytics environment.

Preferred Qualifications

Experience with analytical platforms and BI enablement, including the design and optimization of data capabilities that support Power BI reporting, analytics consumption, and enterprise data products.
Experience with medallion/lakehouse architectures, data contracts, schema evolution, change data capture, event-driven pipelines, data observability, and reliability engineering for enterprise data systems.
Experience with orchestration and transformation tools such as Airflow, Azure Data Factory, Databricks Workflows, or equivalent enterprise data integration tools.
Certifications such as Azure Data Engineer, Databricks Data Engineer, Snowflake SnowPro, Microsoft Fabric Analytics Engineer, or related cloud/data platform credentials are a plus.

Not a 100% match? No worries! Nestlé supports your personal growth with customized development solutions.

What you can expect in your application journey:

1. Hit apply and enter our job portal.

2. Submit your application with your CV.

3. We will contact relevant applicants.

4. Interviews (HR, Hiring team and stakeholders).

5. Feedback.

6. We make an offer.

7. Location dependent checks and pre-onboarding.

8. First working day.

About Nestlé:

We are Nestlé, the largest food and beverage company with brands including KitKat, Nescafé, Maggi, Purina, among many others. We are approximately 275,000 employees strong, motivated by the purpose of enhancing the quality of life and contributing to a healthier future. Our values are rooted in respect: respect for ourselves, respect for others, respect for diversity and respect for our future. With more than CHF 94.4 billion sales in 2022, we have an expansive presence, with 344 factories in 77 countries. Want to learn more? Visit us at www.nestle.com.

We encourage the diversity of applicants across gender, age, ethnicity, nationality, sexual orientation, social background, religion or belief and disability.

Expert Data Scientist (Analytics Data)

Position Snapshot:

Type of Contract: Full Time

Function and Stream: NUSA

Type of work: Hybrid

Work Language: Fluent Business English

The role:

The Expert Data Scientist (Analytics Data) will be responsible for building, maintaining, and optimizing analytical data capabilities that enable scalable data ingestion, transformation, modeling, and access across analytics platforms such as Power BI, Snowflake, Databricks, and Azure. This role develops reusable data models, pipelines, frameworks, automation, and analytical platform patterns that ensure data is reliable, performant, secure, cost-effective, and aligned with enterprise standards for governance, security, quality, and interoperability.

The role will operate as an expert technical contributor, partnering closely with business, analytics, data product, engineering, architecture, security, platform, and regional/global IT stakeholders to strengthen the data foundation for BI, advanced analytics, AI/ML, and enterprise data products.

What you’ll do:

As an Expert Data Scientist (Analytics Data) you will:

Design, build, maintain, and optimize analytical data capabilities that support scalable data ingestion, processing, transformation, modeling, governance, and access across Power BI, Snowflake, Azure Datalake, Databricks, and related cloud data services.
Develop reusable analytical datasets, data pipelines, engineering frameworks, templates, automation scripts, and standard patterns that accelerate delivery while reducing operational friction, duplication, and technical risk.
Optimize Snowflake, Power BI, Databricks, Azure Synapse, and related analytical platform components for performance, reliability, scalability, cost efficiency, observability, and operational resilience.
Embed governance, security, quality, lineage, metadata, access controls, auditability, and compliance requirements into analytical data capabilities and data engineering patterns by design.
Partner with data engineers, analytics engineers, data product teams, architects, platform teams, and business stakeholders to translate business and analytics needs into scalable, reusable, and supportable data capabilities.
Troubleshoot complex data pipeline, analytical platform, integration, access, compute, storage, performance, and reliability issues; lead root-cause analysis and drive durable remediation.
Create documentation, reference implementations, standards, and enablement materials that improve developer productivity, self-service adoption, and consistent use of analytical data capabilities.
Stay current with modern analytical data platform practices, distributed systems, data observability, data contracts, metadata-driven automation, FinOps, MLOps enablement, and platform-as-product operating models.

We offer you:

We offer more than just a job. We put people first and inspire you to become the best version of yourself.

Great benefits including salary and a comprehensive social benefits package. We have one of the best pension plans on the market, as well as flexible remuneration with tax advantages: health insurance, restaurant card, mobility plan, etc.
Personal and professional growth through ongoing training and constant career opportunities reflecting our conviction that people are our most important asset.
Hybrid working environment with flexible working scheme. Our state-of-the-art campus is dog friendly and equipped with a medical center, canteen and areas to co-create network and chill!
Recreation activities such as yoga, Zumba, etc. and a wide range of volunteering activities.

Join our global team of IT professionals at Nestlé, driving daily innovation and leveraging cutting-edge technologies to address digital opportunities. Grow professionally in a dynamic and impactful environment, collaborating with business partners worldwide to deliver integrated technology solutions!

What will make you a great fit?

Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, Data Analytics, or a related field; equivalent experience will be considered.
8+ years of experience in data engineering, analytics engineering, data platform engineering, cloud data platforms, software engineering for data systems, or related technology roles.
Expertise building and optimizing scalable analytical data systems across platforms such as Snowflake, Power BI, Databricks, Microsoft Azure, Spark, SQL-based platforms, cloud storage, and cloud-native data services.
Advanced proficiency with SQL and modern programming languages such as Scala, Python, or Java, with strong software engineering practices for reusable, testable, and maintainable code.
Deep experience designing and operating analytical data platforms, data lakes, lakehouses, data warehouses, hybrid architectures, data pipelines, orchestration frameworks, and enterprise-scale ingestion and transformation patterns.
Strong hands-on experience with batch, streaming, and near-real-time data processing; ETL/ELT frameworks; structured, semi-structured, and unstructured data integration; and high-volume data movement patterns.
Experience with Snowflake capabilities such as warehouse optimization, secure data sharing, role-based access, performance tuning, storage and compute management, and governed data consumption patterns.
Strong knowledge of CI/CD, automation, monitoring, alerting, observability, incident response, root-cause analysis, environment management, and operational excellence practices.
Strong communication, problem-solving, documentation, stakeholder management, and cross-functional collaboration skills, with fluency in English.
Proactive and agile mindset, with the ability to work effectively as an expert technical contributor in a dynamic analytics environment.

Preferred Qualifications

Experience with analytical platforms and BI enablement, including the design and optimization of data capabilities that support Power BI reporting, analytics consumption, and enterprise data products.
Experience with medallion/lakehouse architectures, data contracts, schema evolution, change data capture, event-driven pipelines, data observability, and reliability engineering for enterprise data systems.
Experience with orchestration and transformation tools such as Airflow, Azure Data Factory, Databricks Workflows, or equivalent enterprise data integration tools.
Certifications such as Azure Data Engineer, Databricks Data Engineer, Snowflake SnowPro, Microsoft Fabric Analytics Engineer, or related cloud/data platform credentials are a plus.

Not a 100% match? No worries! Nestlé supports your personal growth with customized development solutions.

What you can expect in your application journey:

1. Hit apply and enter our job portal.

2. Submit your application with your CV.

3. We will contact relevant applicants.

4. Interviews (HR, Hiring team and stakeholders).

5. Feedback.

6. We make an offer.

7. Location dependent checks and pre-onboarding.

8. First working day.

About Nestlé:

We are Nestlé, the largest food and beverage company with brands including KitKat, Nescafé, Maggi, Purina, among many others. We are approximately 275,000 employees strong, motivated by the purpose of enhancing the quality of life and contributing to a healthier future. Our values are rooted in respect: respect for ourselves, respect for others, respect for diversity and respect for our future. With more than CHF 94.4 billion sales in 2022, we have an expansive presence, with 344 factories in 77 countries. Want to learn more? Visit us at www.nestle.com.

We encourage the diversity of applicants across gender, age, ethnicity, nationality, sexual orientation, social background, religion or belief and disability.

Ciudad de Mexico, MX, 11520