technologies-expected :

responsibilities :

owning the Data Engineering team organization that will deliver data needs for different commerce use cases
leading team of experienced data engineers in designing, developing, and delivering scalable, reliable and high performing data pipelines, ETL processes, and data warehouses
hiring, onboarding, mentoring and developing top engineering talent, fostering a culture of learning, collaboration, and continuous improvement
driving operational excellence, including code reviews, design reviews, testing, and deployment processes, to ensure data engineering best practices, standards and processes
elevating the Engineering build / ship mindset in HEINEKEN
overseeing team spirit, performance and providing technical guidance and mentorship to team members, fostering their professional growth & development
implementing good practices, coding standards and modern architecture for DataSecOps
collaborating with stakeholders to understand data requirements and translate them into technical solutions
ensuring the execution of DataSecOps is in place across all teams within a domain and aligned
staying updated on emerging technologies and trends in data engineering and recommending innovative solutions
managing team budgets, including outsourcing partners
organizing and / or participating in hackathons

requirements-expected :

bachelors or masters degree in computer science, Engineering, or related field
in-depth knowledge of and hands-on experience (> 12yrs) in data engineering, with >4 years in leadership or managerial role
proven leadership skills with a track record of building and managing high-performing engineering teams
proficiency in programming languages such as Python, Scala
hands-on experience with data processing frameworks/tools such as Apache spark
strong understanding of distributed computing, data modeling, and database technologies (e.g. SQL, No SQL)
experience with cloud platforms and services, particularly Microsoft Azure, including Azure Data Lake Storage, Azure Databricks, Azure Synapse Analytics, and Azure Data Factory
familiarity with Azure services for data ingestion, transformation, and visualization, such as Azure Event Hubs, Azure Stream Analytics and PowerBI
knowledge of containerization technologies (e.g. Docker, Kubernetes) and their integration with Azure services
experience handling, managing big data using Apache Hadoop, Apache Spark, Apache Kafka
experience serving data with REST APIs and GraphQL (Apollo Client and Apollo GraphOS)
experience work within set Enterprise Architecture guidance and boundaries
have the ability to influence stakeholders as well as balance views
a pragmatic personality, and are a collaborative team player

offered :