Data Engineer

We are looking for an experienced Data Engineer for HEINEKEN, 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: Design, develop, and maintain scalable data pipelines and ETL processes using Azure Data Factory and Databricks. Implement automation and orchestration to streamline data processing.
• Dynamic OpCo Deployments: Refactor existing code and RESTful services to support dynamic OpCo (Operating Company) deployments, enabling multitenant scalability across the platform.
• Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand their data requirements and translate them into technical specifications that drive analytics and machine learning initiatives.
• Optimization & Scalability: Optimize and manage data processing workflows for performance, scalability, and reliability. Implement best practices for efficient data storage and retrieval.
• Data Quality & Validation: Implement robust data quality checks and 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: Monitor, troubleshoot, and optimize data pipelines to ensure timely and accurate data delivery, proactively identifying and addressing potential issues.
• Data Handling: Work with large-scale datasets structured, semi-structured, and 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: Ensure data security and compliance with industry standards and best practices. Implement data governance frameworks and manage data access controls.
• Continuous Improvement: Continuously improve and evolve data engineering 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.