Data Engineer – Data Architecture & Cloud Platforms

InnoWave is looking for an experienced and forward-thinking Senior Data Engineer to design and drive the implementation of complex, scalable, and secure data solutions. If you are passionate about data architecture, cloud technologies, and building robust end-to-end data platforms, and enjoy making strategic technical decisions in a collaborative, international environment, this could be your next challenge!

Senior Data Engineer – Data Architecture & Cloud Platforms

• Analyse, challenge, and clarify business, functional, and non-functional requirements, identifying constraints, dependencies, risks, and architectural considerations.
• Design end-to-end data architectures, covering data ingestion, integration, processing, storage, governance, and consumption.
• Define data models and modelling strategies aligned with business requirements, covering relational, dimensional, document, graph, geospatial, and time-series data models.
• Design and evolve cloud-based data platforms, including Data Lakes, Lakehouses, Data Warehouses, and Data Marts, ensuring scalability, performance, interoperability, and cost efficiency.
• Define data integration solutions using ETL/ELT, batch processing, streaming, Change Data Capture (CDC), APIs, and event-driven architectures.
• Evaluate architectural and technological alternatives, assess trade-offs, and document key decisions through Architecture Decision Records (ADRs) or equivalent documentation.
• Define and promote reference architectures, architectural blueprints, technology standards, and best practices aligned with Enterprise Architecture and Data Management strategies.
• Ensure the implementation of data governance, data quality, metadata management, data lineage, data cataloguing, Master Data Management (MDM), and data security practices.
• Design architectures that meet non-functional requirements, including availability, resilience, scalability, performance, security, disaster recovery, observability, and cost optimisation.
• Define DataOps and observability requirements for data pipelines and datasets, monitoring execution times, latency, data freshness, schema changes, anomalies, and data quality.
• Lead architecture reviews, validate technical designs, identify architectural risks, and guide data engineers, architects, and implementation teams.
• Produce and maintain high-quality architectural documentation, diagrams, technical assessments, and recommendations, communicating decisions effectively to technical and business stakeholders.
• Collaborate with multidisciplinary and international teams, providing technical leadership and promoting knowledge sharing, continuous improvement, and delivery excellence.

InnoWave gives equal opportunity in employment regardless of gender, gender identity, sexual orientation, marital status, race, nationality, religion, age, disability, political beliefs, or any other factor. InnoWave will not pay fees to any third-party agency or company that does not have a signed agreement, do not submit resumes/CV's directly.

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