Data Architect (m/k)

Wymagania: - Strong hands-on experience building modern cloud-native data platforms (AWS preferred). - Expertise in lakehouse or warehouse architectures (e.g. Snowflake, Redshift, Databricks) and modern table formats. - Experience with ELT/ETL tooling, orchestration frameworks, and streaming data. - Solid understanding of MLOps and AI data architectures. - Strong SQL and Python skills; comfortable with DevOps and everything-as-code practices. - Proven ability to design scalable, modular architectures supporting real-time workflows and automation. - Experience standardising data across heterogeneous systems and event-driven environments. - Strong communication skills with the ability to influence technical and non-technical stakeholders. - Hands-on builder with strong ownership. - Automation-first, code-first approach. - Comfortable designing data platforms for AI-native and real-time products. - Not a BI or dashboard-focused role. O firmie: - We recruit the best IT specialists for technology companies – with no risk and full accountability for the outcome. Zakres obowiązków: - Define and evolve the end-to-end data platform architecture, including ingestion, lakehouse/warehouse, transformation, orchestration, governance, observability, and AI enablement. - Establish a unified, standardised data model supporting operational, customer, and supplier workflows. - Lead architectural decisions around storage, table formats, batch and streaming patterns. - Design and implement scalable ELT/ETL pipelines across enterprise systems, network telemetry, and external partners. - Define standards for raw, refined, and curated data layers, ensuring data quality, lineage, and reprocessability. - Introduce CDC, schema evolution, and automated ingestion patterns. - Architect the data foundations for AI and ML, including feature stores, model lifecycle, and ML observability. - Enable AI-driven use cases such as pricing intelligence, prediction, automation triggers, and real-time insights. - Support semantic and conversational data access for intelligent workflows. - Design scalable data governance and metadata architectures, including catalogues, lineage, and ownership. - Implement automated data quality checks and observability embedded in pipelines. - Act as the technical authority for data architecture decisions across teams. - Guide data engineers, ML engineers, and analysts through standards and best practices. - Partner with platform, product, and operations teams to make data a first-class capability. Oferujemy: - International, collaborative work environment. - Exposure to large-scale cloud, data, and AI platforms. - Strong learning and development support. - Competitive compensation and benefits. - Hybrid work.