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Salary
≈ $29k – $53k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Architect
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Oct 6, 2026. NTT DATA scores A on the Alion truth index.

Overview
Company
Impact
Profile match
NTT DATA is a Tokyo system integrator founded in 1988 that spun out of the data communications arm of NTT. It is one of the largest information technology services firms in the world, building banking, public sector and payment systems and operating global consulting and managed services. The company runs the CAFIS payment network used across Japanese retail and banking.
Backed by Pamlico Capital

India T&M Special Bonus:

Technical Solution Architect

Job Description

Define and govern the end-to-end technical architecture for the monitoring solution. Translate SOW requirements into an integrated design covering SSAS DMVs, Extended Events, ALETL logs, SQL Server telemetry storage, time-series analysis, thresholds, Power BI reporting, security, deployment, and operational support.

Provide technical leadership across Data Architecture, SQL Engineering, SSAS Monitoring, Power BI, and QA workstreams. Establish engineering standards, review technical deliverables, resolve cross-workstream dependencies, and ensure consistent implementation of monitoring metrics, baselines, thresholds, RAG status, historical trends, auditability, restartability, and security. Support technical discovery, testing, deployment, production validation, documentation, knowledge transfer, and operational handover.

Key Responsibilities

  • Define the end-to-end solution architecture for collecting, processing, storing, and visualising monitoring data.
  • Design integration across SSAS DMVs, SSAS Extended Events, dbo.ALETL_Log, SQL Server, SQL Agent, Git, DACPAC, and Power BI.
  • Define the architectural approach for raw, staging, curated, configuration, dimension, fact, snapshot, audit, exception, and serving layers.
  • Ensure the solution supports time-series capture, datetime filtering, historical trending, baseline comparison, threshold evaluation, RAG status, and capacity analysis.
  • Define non-functional requirements covering performance, scalability, security, availability, auditability, restartability, retention, supportability, and recovery.
  • Define technical patterns for scheduling, watermarking, duplicate prevention, exception handling, safe reruns, operational logging, and failure recovery.
  • Translate SOW requirements into implementable technical work packages and acceptance criteria.
  • Lead technical discovery and validate the availability, quality, and suitability of SSAS, ALETL, SQL Server, and Power BI data sources.
  • Establish architecture, design, development, naming, coding, testing, deployment, and technical-review standards.
  • Review and approve data models, source-to-target mappings, T-SQL, SSAS collectors, Extended Events sessions, derived metrics, DAX measures, security design, and deployment artefacts.
  • Ensure consistent implementation of metric definitions, baseline classes, warning and critical thresholds, severity, RAG calculations, and historical trends.
  • Resolve technical issues and dependencies across Data/SQL, SSAS, Power BI, and QA workstreams.
  • Provide technical direction during developer testing, SIT, UAT, engineering defect resolution, deployment, rollback, hypercare, and production validation.
  • Ensure least-privilege access for SQL Server, SSAS, service accounts, Power BI, Git, and deployment processes.
  • Ensure the solution remains within approved SOW scope and technical exclusions.
  • Review as-built documentation, operational runbooks, troubleshooting guidance, and knowledge-transfer material.

Skill Set

  • Strong SQL Server and SSAS solution architecture experience
  • SSAS Multidimensional, DMVs, Extended Events, XMLA, cubes, dimensions, measure groups, and partitions
  • Monitoring, observability, telemetry, and time-series architecture
  • SQL Server data architecture and dimensional modelling
  • Processing-event correlation, historical baselines, thresholds, severity, and RAG design
  • Integration patterns covering SQL Server, SQL Agent, SSAS, ALETL logs, and Power BI
  • Security, RBAC, service accounts, least-privilege access, and auditability
  • Performance, scalability, retention, restartability, recovery, and supportability design
  • Advanced understanding of T-SQL, stored procedures, indexing, and query optimisation
  • Power BI semantic-model, DAX, RLS, gateway, refresh, and workspace-governance concepts
  • SSDT, Git, DACPAC, database deployment, rollback, and release governance
  • Technical design reviews, quality gates, testing assurance, and production readiness

Strong problem-solving, technical documentation, workshop facilitation, and stakeholder communication

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