Digital & Technology Team (D&T) is an integral division of HEINEKEN Global Shared Services Center. We are committed to making Heineken the most connected brewery. That includes digitalizing and integrating our processes, ensuring best-in-class technology, and embedding a data-driven culture. By joining us you will work in one of the most dynamic and innovative teams and have a direct impact on building the future of Heineken!
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Commerce DevOps Hub is being established. The newly created organization, being an integral part of the Global Digital & Technology Function, is tasked with maintaining, but most importantly developing (functionally and technologically) IT solutions supporting the Commerce area at Heineken. Commerce DevOps Hub is located in Kraków and will include highly qualified IT professionals with direct contribution to both the technological development of the Heineken Commerce and the Hub itself.
As the Senior Data Engineer in the Data Foundation scope, you have in-depth knowledge of the technical details and how the products work, and you will act as an expert in the team responsible for the technical configuration, development and integration of products and platforms based on our tech stack, used by specific business processes across OpCos, to better serve their customers.
You will provide expert guidance and ensure alignment with architecture and business objectives and ensure on-time delivery. You drive the end-to-end operations of the platforms, keeping them streamlined, structured, and within service level agreements.
You will collaborate closely with other Data and Analytics teams for efficient development pipelines. You will work directly with the Product Owner(s) and Product Architect(s), understanding the business needs and translating them into specifications and services in line with overall engineering standards and roadmaps.You will be expected to be implementing new features, deliver high quality code, follow the agile methodologies and be a team player. The most important part is to be part of the team effort towards value-driven outcomes and the successful completion of tasks. Your proactive approach will be key in maintaining comprehensive documentation and collaborating with your team members through offering help, raising question and actively taking part in all activities. You will serve as a key contributor in refining and driving excellence in solution engineering practices to deliver high-quality solutions throughout the software development lifecycle in our Data landscape.
The role reports directly to the Data Engineering Lead or Chapter Lead.
Your responsibilities would include:
coach and Mentor a team of experienced team members of Data Engineers in designing, developing, and delivering scalable, reliable, and high performing big data solutions
coach and Mentor the design, development, and maintenance of scalable data pipelines and ETL processes. Monitor and optimize data infrastructure performance, identifying and resolving bottlenecks and issues
coach and Mentor the team from a technical standpoint, and drive operational excellence, including code reviews, design reviews, testing, and deployment processes
be an individual contributor (~60%) engineering the software products/solutions, jointly with the team
ensure that the team adheres to coding standards, best practices, and architectural guidelines, oversee team spirit and team performance, guide and mentor team members
oversee the implementation of the technical architecture, solve immediate technical challenges
implement good practices, coding standards and modern architecture for DataOps; be a “go-to-person for technical decisions and problem-solving within the team
ensure that the execution of DevSecOps is in place in the team's daily work
inspire, advise, and drive the selection of development approach
coordinate software development and address technical debt in the team
hire, onboard, mentor, and develop top engineering talents, fostering a culture of learning
collaboration, and continuous improvement
take Lead when needed in technical discussions with other teams/departments and oversees state-of-art quality of the stack
may be involved in cross-functional discussions, representing the domain in broader technical discussions across domains
responsible for designing and improving processes that enhance efficiency and quality
communication with Engineering Manager, Product Owner, Business Analyst and Scrum Master to align on project. / sprint goals, timeline and resource allocation
You are a good match if you have:
8+ years of experience in Data Engineering, with a strong understanding of data integration, ETL processes, and data warehousing.
hands-on experience and in-depth knowledge of the technologies listed as mandatory in the Technology Stack section
strong understanding and implementation of software development principles, coding standards, and modern architecture
familiarity with data governance and compliance standards.
hands-on experience in implementing and managing End-to-End DataOps / Data Engineering projects in a team
proven ability to lead software development teams of engineers with varying experience and adapt to team sizes from small to large
experience in working in diverse projects with varying technologies, products, and systems
strong problem-solving skills and ability to make critical technical decisions
ability to guide / mentor other team members
effective communication and interpersonal skills, with the ability to collaborate with technical and non-technical stakeholders.
proven ability to demonstrate that can work independently and a self-starter
pragmatic, and collaborative team player
You are a good match if you know:
Must have (all levels):
proficiency in programming languages such as Python, SQL, and experience with big data technologies like Hadoop, Spark, and Kafka
experience with cloud platforms (e.g., AWS, Azure, GCP) and data storage solutions (e.g., Databricks, BigQuery, Snowflake)
experience with CI/CD processes and tools, including Azure DevOps, Jenkins, and Git, to ensure smooth and efficient deployment of data solutions
familiarity with APIs to push and Pull data from data systems and Platforms
familiarity with understanding software architecture High level Design document and translating them to developmental tasks
Nice to have:
Familiarity with Microsoft data stack such as Azure Data Factory, Azure Synapse, Databricks, Azure DevOps and Fabric / PowerBI.
Experience with machine learning and AI technologies
Data Modelling & Architecture
ETL pipeline design
Expert in Python, Pyspark and SQL
Azure Data Factory
Azure DevOps
Logging and Monitoring using Azure / Databricks services
Apache Kafka
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