Connected Brewery Tech Lead - IoT Data Platform

Nasze wymagania:
You are a good candidate if you have:
Qualifications
* Minimum 10 years of experience across Data Engineering, Data Platform Engineering, Analytics Engineering, BI Engineering, Data Science Enablement, or similar data and analytics roles
* At least 3 years of technical leadership experience in a complex data, analytics, BI, AI/ML, or platform delivery environment
* Proven experience leading, line-managing, or formally coordinating mixed technical teams, including performance management, coaching, capability planning, and work allocation
* Experience defining standards, reusable methods, architecture patterns, governance practices, and production-readiness expectations across multiple teams, sites, markets, or business units
* Experience managing delivery across multiple stakeholders, squads, technical disciplines, and enterprise platforms
Experience / Skills:
* Working across multiple environments such as development, test, staging, and production
* Designing pipelines that support multiple consumers and use cases
* Understanding how to build scalable and reusable data processing patterns
* Understanding how curated datasets are consumed by BI and analytics teams
* Supporting BI Developers in building reliable reporting and semantic-layer outputs
* Supporting the creation of trusted datasets for BI, dashboarding, and advanced analytics
* Helping reduce duplication across reports, datasets, and squad-specific logic
* Ensuring that reporting and analytics requirements are considered when designing upstream data pipelines
* Supporting alignment between operational reporting, historical reporting, and advanced analytics use cases
* Unit and integration testing for data pipeline, with data lineage and traceability
* Pipeline observability and operational monitoring
* Reconciliation between source and target datasets
* Handling pipeline failures, retries, and support processes
* Ensuring transformation logic and data dependencies are documented
* Supporting production readiness and handover of data products
* Ensuring reporting and analytical outputs are based on trusted and well-understood data

Mile widziane:
AWS Step Functions
EventBridge or event-driven data processing
Lambda-based orchestration or lightweight integration patterns
Iceberg, Delta, or similar table formats
CI/CD deployment of AWS data engineering workloads
Terraform-based AWS infrastructure deployment
Understanding of Azure data platform concepts
Working with Azure Data Lake, Azure Data Factory, Synapse, Fabric, or similar services
Preparing data for semantic-layer or reporting consumption
Supporting BI and analytics teams with curated, trusted, and model-ready datasets
Understanding how data needs to be structured for Power BI or advanced analytics use cases
Helping align AWS data preparation with Azure-based consumption patterns
Understanding the hand-off between data engineering outputs and semantic-layer modelling
Power BI exposure
Semantic model / semantic layer experience
Experience supporting advanced analytics teams
Experience with operational dashboards or Grafana
Experience with KPI and metric standardisation across multiple sites or OpCos.

O projekcie:
We are looking for a Connected Brewery Tech Lead to own the technical direction, production readiness, and capability leadership for the Data Engineering, BI Development, and Data Science chapter supporting the Connected Brewery data product ecosystem.
The role is accountable for setting and governing data and analytics standards, reusable architecture patterns, delivery methods, and production-readiness expectations across a multi-OpCo, multi-brewery, multi-use-case ecosystem. Connected Brewery should be treated as a scalable data product landscape, not as a single delivery stream.
The role ensures that data pipelines, BI outputs, semantic-layer inputs, analytical solutions, and machine-learning-ready datasets are scalable, reusable, reliable, observable, secure, supportable, and designed for adoption across multiple breweries and OpCos.
The role is centred on building durable data foundations and reusable analytics capabilities across extraction, transformation, storage, quality assurance, integration, deployment, operational support, stakeholder engagement, and capability building across data professionals.

Zakres obowiązków:
Chapter Leadership and People Management
Leading and line-managing approximately 4-10 Data Engineers, BI Developers, and Data Scientists, including work allocation, coaching, performance management, development planning, and capacity planning
Ownership of the chapter operating model, capability plan, skill matrix, succession risks, and hiring needs for the Connected Brewery data and analytics capability
Setting technical expectations for chapter members and ensure consistent engineering, BI, analytics, documentation, and production-support practices
Governing vendor and contractor contribution where applicable, ensuring external delivery capacity follows chapter standards and contributes to reusable assets
Definition and governance of the reusable data product patterns, architecture principles, semantic-layer inputs, BI delivery standards, and analytical delivery methods across breweries, OpCos, and use cases
Approving key architecture patterns and manage technical trade-offs between tactical squad delivery, long-term scalability, operational supportability, and platform direction
Leading cross-squad dependency management, delivery prioritisation, technical risk resolution, and alignment across squads, platform teams, breweries, and OpCos
Ensuring that Connected Brewery evolves as a scalable data product ecosystem with reusable methods, components, templates, and standards that can be adopted beyond individual sites.Scalable Data and Analytics Delivery
Driving the delivery of scalable data pipelines, curated datasets, semantic-layer inputs, BI outputs, advanced analytics outputs, and machine-learning-ready data assets
Setting standards for reusable, trusted, observable, supportable, secure, and cost-conscious data products and pipelines
Ensuring data and analytics delivery is designed for repeated adoption across multiple use cases, breweries, countries, and OpCos
Owning alignment between AWS-based data engineering patterns and Azure-based semantic-layer, BI, and downstream analytics consumption requirements
Reducing duplication across reports, datasets, metric definitions, transformation logic, and squad-specific implementations by enforcing common reusable patterns
Accountability for data quality, lineage, observability, testing, monitoring, documentation, and production-readiness standards across data products and pipelines
Ensuring technical decisions, dependencies, transformation logic, design assumptions, support models, and downstream impacts are documented and governed

Oferujemy:
Hybrid ways of working
Private medical healthcare
Attractive performance bonus
Sodexo pre-paid card
Life insurance
Employee referral program
Wide range of trainings
Local and global job opportunities within HEINEKEN
Parking space
Open bar once a week
We are ACCA Approved Employer