Teradata Solution Architect

We are looking for a Teradata Solution Architect to own design decisions, assessment of the existing data landscape, and modernization of large-scale Teradata data warehouse environments. The ideal candidate will own current-state analysis, define the target-state architecture, and produce the technical implementation roadmap, then present and defend those decisions to executives, business teams, and architecture board.

• Lead the end-to-end architecture, assessment, modernization, migration, and transformation of large-scale Teradata data warehouse environments.
• Assess current-state data platforms, workloads, integrations, performance, capacity, and technology gaps, and define the target-state architecture and implementation roadmap.
• Design scalable enterprise data architectures integrating Teradata with Hadoop/Cloudera, on-premises object storage, cloud lakehouse platforms, MPP databases, and other data platforms.
• Define workload placement, capacity planning, cost optimization, archival, offloading, and hybrid/cloud migration strategies.
• Architect Teradata Vantage and legacy platforms, including Intelli Flex and Vantage Cloud, with appropriate migration and upgrade paths.
• Design and optimize Teradata physical models covering PI, NUPI, No
  
  PI, PPI, multi-level partitioning, join/hash/sparse indexes, compression, and statistics.
• Diagnose and resolve performance issues involving skew, spool, redistribution, duplication, and workload contention using DBQL, TASM, Workload Designer, and related tools.
• Architect high-volume data pipelines integrating heterogeneous telecom source systems using TPT, BTEQ, Informatica, AbInitio, Kafka/CDC, APIs, and other integration technologies.
• Define load, error-handling, restart/recovery, reconciliation, audit, and SLA-driven batch processing strategies.
• Design interoperability solutions using Query Grid, Native Object Store, Data Mover, Viewpoint, and data virtualization technologies.
• Develop telecom data architectures covering billing, mediation, interconnect, CRM, DPI, network performance, customer experience, CDR processing, churn, ARPU, and network KPI analytics.
• Apply the Communications Logical Data Model (CLDM) and industry analytical schemas across enterprise data platforms.
• Define data governance, metadata, lineage, business glossary, stewardship, and impact-analysis operating models.
• Architect automated end-to-end lineage across ETL, data pipelines, transformations, and consumption layers using tools such as Informatica EDC/Axon/CDGC, Collibra, and Alation.
• Design audit, reconciliation, Row-Level Security, Secure Zones, Access Logging, DBQL, and PDCR capabilities while considering performance and SLA impact.
• Evaluate and architect cloud and lakehouse modernization solutions using object storage such as MinIO/Ozone and open table formats including Iceberg, Delta Lake, and Hudi.
• Architect governed semantic and consumption layers supporting Power BI, Qlik, Micro Strategy, and other enterprise BI platforms.
• Lead legacy platform decommissioning, migration, consolidation, and modernization initiatives.
• Evaluate data mesh and data product operating models and identify appropriate enterprise use cases.
• Present and defend architecture decisions, technical roadmaps, risks, costs, and trade-offs to C-level stakeholders, business teams, and architecture boards.
• Establish architecture standards, design principles, technology selection criteria, and governance frameworks.
• Provide technical leadership and mentoring to data architects, engineers, and technical teams.

• 12+ years of experience in enterprise data warehousing, data architecture, or platform architecture.
• 8+ years of hands‑on experience with Teradata data warehousing and modern data/lakehouse platforms.
• Proven experience delivering large‑scale data warehouse or analytics solutions within the telecommunications sector.
• Experience with at least two national/operator‑scale telecom engagements involving substantial subscriber volumes.
• Strong experience architecting data pipelines across multiple heterogeneous source systems.
• Hands‑on experience with multi‑engine data estates involving Teradata, Hadoop/Cloudera,…