What You Will Do Design and implement scalable data ingestion pipelines for structured and unstructured data sources, including manufacturing systems, edge devices, and enterprise data platforms, ensuring consistent data quality from source to consumption Build and maintain both batch and streaming data pipelines for analytics and AI use cases, leveraging cloud-native tooling on Microsoft Azure and/or AWS Design and expose REST or GraphQL APIs for data assets, machine learning model endpoints, and AI services, enabling reliable, governed consumption by internal applications and analytical systems Implement CI/CD practices and DataOps principles across pipeline development and deployment, supporting automated testing, versioning, and release management for data infrastructure Ensure data quality, lineage, and observability across all pipelines, implementing monitoring and alerting that surfaces data issues before they affect AI or analytics outputs Support the integration of manufacturing and edge device data, including IoT and OT systems, into the central data platform, addressing the specific latency, format, and volume challenges of operational technology environments Collaborate with data scientists and AI engineers to design and optimise data flows that support model training, inference, and knowledge retrieval pipelines Apply security-by-design practices to all pipeline and API design, including access control, encryption, and protections against data leakage, in line with Intersnack's sovereignty and compliance standards Contribute to the AI literacy and enablement programme by supporting colleagues in understanding data pipeline health, data quality standards, and the role of reliable data in AI outcomes Essential Skills & Experience Proven experience designing and implementing production-grade data pipelines using cloud-native services on Microsoft Azure (e.g., Azure Data Factory, Azure Event Hubs, Databricks) and/or AWS (e.g., AWS Glue, Kinesis, Lake Formation) Strong proficiency in at least one pipeline or transformation framework (e.g., Apache Spark, dbt, Apache Kafka, or equivalent) and a scripting language such as Python or Scala Solid hands-on experience with SQL and NoSQL databases (e.g., PostgreSQL, Cosmos DB, MongoDB, or equivalent), including data modelling and query optimisation for both transactional and analytical workloads Experience building and maintaining streaming and batch pipelines for analytics and AI applications, with an understanding of trade-offs between the two approaches Ability to design and implement REST or GraphQL APIs for data and model serving, with an understanding of API versioning, documentation, and governance Familiarity with DataOps and CI/CD practices as applied to data engineering, including automated testing, pipeline orchestration, and infrastructure-as-code Experience with data quality tooling, lineage tracking, and observability frameworks (e.g., Great Expectations, OpenLineage, or equivalent) Working knowledge of AI and data security fundamentals, including data access controls, encryption, and risks such as data exfiltration in pipeline contexts Awareness of GDPR, EU AI Act, and EU data sovereignty requirements and their implications for data infrastructure design A strong command of spoken and written English is required; knowledge of German is considered an advantage Valuable Experience Experience working with manufacturing or operational technology (OT) data environments, including IoT/edge device data ingestion and time-series data handling Familiarity with Microsoft Fabric, OneLake, or Azure Purview for unified data platform management Exposure to MLOps practices, including data versioning, feature stores, or model monitoring pipelines Experience with Terraform or other infrastructure-as-code tooling for scalable, repeatable data infrastructure deployment Background in FMCG, manufacturing, or supply chain, providing context for the operational data challenges typical in these environments Important: Please note that a valid work and residence permit is required for non-EU applicants for this position.
Successfully and sustainably growing, our turnover in 2024 was more than €4.5 bn. We are now present in more than 30 countries across Europe and beyond. We have 12 regional Management Units, 45 production sites, and a total workforce of approximately 15,000 people worldwide. For further company insights, please visit the following link: Intersnack Group Overview If you want to become part of our dynamic food industry success story, you’ll find all sorts of opportunities at Intersnack.