Data Platform Developer - REF5116I

As Hungary’s most attractive employer in 2025 (according to Randstad’s representative survey), Deutsche Telekom IT Solutions is a subsidiary of the Deutsche Telekom Group. The company provides a wide portfolio of IT and telecommunications services with more than 5300 employees. We have hundreds of large customers, corporations in Germany and in other European countries. DT-ITS recieved the Best in Educational Cooperation award from HIPA in 2019, acknowledged as the the Most Ethical Multinational Company in 2019. The company continuously develops its four sites in Budapest, Debrecen, Pécs and Szeged and is looking for skilled IT professionals to join its team.

We are seeking an experienced Data Platform Developer to strengthen the clarity and consistency of our cloud-based Lakehouse platform architecture. Your primary mission is to define, evolve, and enforce platform-level architectural standards and contracts, so teams build solutions consistently and transparently - with a shared understanding of what belongs where, why it belongs there, and how it moves through the platform. A key focus is establishing clear semantics and promotion rules across our layered data architecture (from raw ingestion to curated, consumption-ready data).

As part of the Common Data Intelligence Hub, you will collaborate with data architects, data engineers, analytics engineers, and solution designers to drive a target platform architecture and an architectural runway (platform enablers) that unlocks future use cases - without owning day-to-day development or operations.

Responsibilities

• Define, document, and continuously refine layer semantics and promotion rules across Landing, Sources, Bronze, Silver, and Gold (what belongs where quality gates, required metadata, and readiness criteria, and ensure these rules are embedded in governance tooling such as Databricks Unity Catalog or Microsoft Fabric OneLake.
• Establish and govern platform guardrails and contracts, including schema evolution, CDC principles at platform level, data/interface contracts between layers, and key non-functional requirements (reliability, performance, security, cost).
• Own and evolve the platform reference architecture, including capability/service boundaries, responsibilities, standard integration patterns, and architectural standards.
• Drive the target platform architecture and an incremental roadmap towards it, maintaining a prioritized architectural runway of platform enablers and technical debt initiatives.
• Support and review solution designs for new use cases, ensuring alignment with platform standards, governance requirements, and the layered architecture.
• Establish an architecture documentation practice that remains current and usable (templates, ADRs, review checklists, clear artifact ownership, and regular drift checks).
• Ensure consistent representation of the platform within enterprise architecture tooling and processes (e.g., LeanIX), and act as the interface to enterprise architecture stakeholders.
• Partner with Data Architects and domain teams to ensure platform rules enable high-quality modelling and cross-domain consistency - while keeping ownership of business semantics/canonical models with the Data Developer role.

• 3-5 years of experience in data platform architecture, including at least 2 years in cloud-based data architecture (Lakehouse/Data Warehouse/Data Lake).
• Proven ability to define and enforce architecture standards that are adopted across teams (guardrails, review gates, exception handling).
• Strong understanding of Lakehouse concepts including layering, governance, schema evolution, CDC implications, and operational quality attributes.
• Experience collaborating with cross-functional stakeholders (engineering teams, governance/security, enterprise architecture, product/domain stakeholders).
• Excellent communication skills in English (spoken and written), able to make complex architecture understandable and actionable.
• Hands-on experience with Agile development methodologies (SAFe, TOGA, SCRUM, KANBAN, etc.).

Skills   

• Cloud data ecosystem architecture, e.g. Azure (ADF, Databricks, Unity Catalog), AWS (Glue, EMR, Lake Formation), or Google Cloud (Dataflow, Dataproc, Dataplex) and comparable Lakehouse governance patterns.
• Architecture standards & documentation as code (ADRs, templates, structured diagrams, versioned documentation).
• Platform-level governance patterns (catalog, access controls, auditability, lineage concepts).
• Data engineering architecture fundamentals (batch/streaming trade-offs, reliability patterns, observability requirements, schema evolution).
• Defining layer semantics and platform contracts that reduce ambiguity and enable scale.
• Translating target architecture into a practical roadmap (runway/enablers, sequencing, trade-offs).
• Solution design facilitation and review (focus on platform conformance and long-term maintainability).
• Systems thinking and strong conceptual clarity; ability to turn ambiguity into crisp rules and boundaries.
• Influencing without authority; facilitation across multiple teams and domains.
• Pragmatism: balances architectural idealism with delivery constraints and incremental progress.
• Ability to work in cross-functional teams and support collaborative knowledge transfer.

• Solution Design knowledge is advantage.

* Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation.