Data Solution Architect

To strengthen our internal IT Expert team, we are looking for a Data Solution Architect for our parnter's project in the communication sector.

The role acts as the primary architectural bridge between business demands (Commercial, Customer Value Management, Finance, Analytics, AI teams) and data engineering delivery (Data Engineering squads, DWH/Lakehouse teams, System Integrators, and Cloud specialists).
The Data Solution Architect translates analytical and operational data requirements into scalable, secure, governed, and operationally sustainable end-to-end High-Level Designs (HLDs)—supporting the strategic transition from legacy on-prem DWH platforms to a modern Cloud Data Lakehouse, Semantic Layer, and AI-ready data mesh.

Tasks:

- End-to-End Data Solution Design: Designs end-to-end data pipelines and architectures spanning source system extraction, real-time streaming/batch ingestion, staging, transformation, storage tiers (bronze/silver/gold), semantic modeling, and business consumption (BI, CVM, AI/ML).
- Lakehouse & Semantic Architecture: Architectures modern cloud-native Data Lakehouse solutions (AWS, S3, Redshift/EMR/Athena) and designs enterprise semantic/business layers and reusable Data Products.
- Legacy DWH Modernization & Migration: Defines technical migration patterns, dual-run architectures, data cutover strategies, reconciliation mechanisms, and historical data archiving from legacy DWH/relational platforms (e.g., Teradata, Oracle, MSSQL) to the Cloud Lakehouse.
- Target Architecture & Layer Alignment: Ensures all data solutions comply with the Target Architecture, Data & AI Layer blueprints, Enterprise Data Model (EDM), and cloud infrastructure guardrails.
- Data Governance, Lineage & Security by Design: Embeds automated metadata management, end-to-end data lineage, data quality monitoring, data stewardship, data retention policies, and security/privacy controls (RBAC/ABAC, masking, GDPR, data classification) directly into solution designs.
- Architecture Review Board (ARB) Defense: Presents, justifies, and defends project-level data solution designs and Data ADRs/KDDs at the ARB/TAB for formal architectural approval; manages architectural conditions, risks, and technical debt resolution.
- AI & Advanced Analytics Enablement: Integrates data architectures with upstream/downstream Machine Learning, Feature Stores, Knowledge Graph models, and RAG/LLM context pipelines in collaboration with the Data & AI Lead Architect.
- Delivery & Operational Readiness: Provides architectural guidance to data engineers and delivery squads during development, testing, data reconciliation, and operational transition (DataOps, alerting, SLO/SLA management) to ensure technical delivery remains faithful to the approved HLD and architectural guardrails.
- Cross-Domain Collaboration: Works closely with Lead Architects (Layer Owners), Chief IT Architect, Information Security, Infrastructure/Cloud teams, and external technology partners/vendors (e.g., COTS vendors, CETIN, system integrators) to resolve architectural trade-offs, dependencies, and risks. Reports dotted line to IT Architecture Office in the context of architecture governance matters.
- Non-Functional Requirements (NFR) Ownership: Defines, validates, and guarantees non-functional requirements within the solution scope, including high availability, disaster recovery, performance (e.g. query performance, ingestion throughput, pipeline processing windows, data freshness/lag, storage cost optimization, retention rules), scalability, observability, security baselines, and data privacy (GDPR).

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or related field.
• 4+ years of proven experience as a Data Solution Architect, Data Architect, or Senior Data Engineer designing large-scale enterprise data and analytics platforms.
• In-depth expertise in modern Data Lakehouse and Cloud Data Warehouse architectures, preferably on AWS (S3, Redshift, Glue, Athena, EMR, Lake Formation, Kinesis/MSK).
• Strong background in data modeling techniques (Dimensional/Kimball, Data Vault 2.0, 3NF, Semantic Layer modeling, Data Product contracts).
• Hands-on experience with legacy enterprise DWH modernization, ETL/ELT pipelines, streaming data architectures (Kafka / EventBridge), and data reconciliation frameworks.
• Solid understanding of Data Governance tooling and practices (Data Catalogs, Lineage, Data Quality frameworks, GDPR compliance, Role/Attribute-Based Access Control).
• Familiarity with Knowledge Graphs, Vector search, RAG architectures, and AI/ML data integration is a strong advantage.
• Experience in telecommunications data domains (CDR processing, Billing/Charging data, CVM, BSS/OSS data structures, TM Forum SID) is a plus.
• Ability to work effectively in cross-functional agile squads and international vendor environments.
• Excellent communication, presentation, stakeholder management, and technical documentation skills in English and Hungarian.

Location & onsite ratio:

• 2-3 days onsite at the Törökbálint office