Senior Data Engineer - Promo Advisor

Senior Data Engineer

About the Global Analytics Team

The mission of Global Analytics is to lead HEINEKEN into becoming a data-driven company and the best-connected brewer. As a team, we foster a data-driven entrepreneurial culture across the company. We act as an incubator for smart data products in all business areas from sales to logistics, marketing, and purchasing rapidly launching value-creating use cases, such as optimized spare parts management and

smarter media spending. This year, our focus is to scale these and other use cases to as many countries as possible around the globe.

Our team comprises data scientists, engineers, business intelligence specialists, and analytics translators, working together to deliver data-driven solutions across the business. We operate across three continents, with satellite teams in South Africa, Poland, India, and Singapore. We are collaborative, innovative, and reliable, embracing diverse cultures and perspectives. We strive to create an environment where team

members enjoy both the challenges they tackle and the people, they solve them with. We innovate to transform HEINEKEN from a traditional to a data-driven company. We position ourselves as a business partner, driving value-creating decisions and building trust in our solutions. If these challenges sound interesting and exciting, we invite you to apply. We have ambitious goals, and we need your help to achieve them. Position Overview We are looking for an experienced Senior Data Engineer with a deep understanding of Azure and Databricks platforms. The ideal candidate will have at least 8 years of experience in data engineering, with expertise in designing, developing, and maintaining data pipelines, optimizing data processing workflows, and ensuring the reliability and

scalability of our data infrastructure.

Key Responsibilities

Data Pipeline Development:

pipelines and ETL processes using Azure Data Factory and Databricks. Implement

automation and orchestration to streamline data processing.

Dynamic OpCo Deployments:

support dynamic OpCo (Operating Company) deployments, enabling multitenant

scalability across the platform.

Collaboration:

stakeholders to understand their data requirements and translate them into

technical specifications that drive analytics and machine learning initiatives.

Optimization & Scalability:

performance, scalability, and reliability. Implement best practices for efficient

data storage and retrieval.

Data Quality & Validation:

processes to ensure the accuracy, consistency, and integrity of data across

pipelines. Update and refine code testing strategies to continually improve data

quality and reliability.

Monitoring & Troubleshooting:

pipelines to ensure timely and accurate data delivery, proactively identifying and

addressing potential issues.

Data Handling:

unstructured to support various analytics, machine learning, and business

intelligence initiatives. Integrate new data pipeline executions with the HDP

Upload Portal to streamline data ingestion and ensure seamless pipeline

execution.

Security & Compliance:

standards and best practices. Implement data governance frameworks and

manage data access controls.

Continuous Improvement:

practices, tools, and processes. Stay up to date with the latest developments in

Azure, Databricks, and data engineering technologies.

Required Qualifications

Education: Bachelor's degree in computer science, Engineering, Information

Technology, or a related field.

Experience: Minimum of 8 years of experience in data engineering, including

hands-on work with Azure Data Factory, Azure Databricks, and other Azure data

services.

Technical Proficiency: Strong SQL skills and experience with database

technologies such as Azure SQL Database or SQL Server, and familiarity with big

data processing frameworks like Apache Spark.

Programming Skills: Proficiency in one or more programming languages (such as

Python, Scala, etc.,), with an emphasis on writing clean, efficient, and scalable

code.

Data Modelling: Strong understanding of data warehousing concepts and data

modelling, with experience in creating and managing enterprise data warehouses.

Problem-Solving: Excellent problem-solving skills with the ability to work

independently as well as in a collaborative team environment.

Communication: Strong communication skills with the ability to effectively

collaborate with both technical and non-technical stakeholders to drive project

success.

Preferred Qualifications

Azure Synapse Analytics: Experience with data integration, warehousing, and

analytics using Azure Synapse.

Data Governance & Security: Knowledge of data governance, data security, and

compliance best practices, and experience implementing these in a data

engineering context.

DevOps & CI/CD: Familiarity with CI/CD pipelines and DevOps practices for data

engineering, including version control, automated testing, and continuous

deployment.

Multi-Cloud Experience: Experience with other cloud platforms such as Azure,

AWS or GCP is a plus, bringing additional versatility to the role.

What We Offer

Innovative Environment: Work in a dynamic environment where cutting-edge

technology and innovation are at the heart of everything we do.

Professional Growth: Opportunities for continuous learning, professional

development, and career advancement within a rapidly growing company.

Collaborative Culture: Be part of a diverse, creative team that values initiative

and collaboration.

Comprehensive Benefits: Competitive salary, comprehensive health benefits,

retirement plans, and other perks to support your work-life balance.

Join Our Team

If you are passionate about data engineering and excited to work with Azure and

Databricks to build scalable data solutions, we invite you to apply. Join us and contribute

to our mission of leveraging data to drive business transformation.