Senior Business Intelligence Analyst

NextGenEnergyJobs; Mumbai; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

NTT Global Data Centers is seeking a Senior Business Intelligence Analyst to define, design, and implement end-to-end use-cases on a global data repository and reporting platform. You will act as a solution architect translating business requirements into robust designs and ensuring architectural integrity across releases.

Responsibilities include leading data ingestion pipelines, semantic models, and delivering value-driven visualizations and outputs, with a focus on secure, scalable analytics

Qualifications

• Bachelor's degree in a relevant field; advanced degree advantageous.
• Experience translating business needs into end-to-end analytics solutions.
• Strong experience with BI tools and data platforms.

Responsibilities

• Define and own the solution architecture for semantic parts and use cases on the reporting platform.
• Design scalable data architecture patterns aligned with enterprise standards.
• Translate requirements into end-to-end technical designs and lead PoCs for new technologies.
• Collaborate with IT Data Foundation for ETL and governance.
• Provide architectural oversight for support and enhancements.

Skills

Power BI

SQL

Data Modeling

Data Governance

Azure Data Factory

Databricks

DAX

Communication

Education

Bachelor's in Computer Science/Information Systems/Engineering

Tools

Excel

Microsoft Fabric

Azure Data Engineer

Job description

Join NTT Global Data Centers and be part of a team that drives innovation and sustainability in the digital world.

Responsibilities

• The Senior Business Intelligence Analyst is accountable for defining, designing and implementing end to end use-cases on our global, cross functional data repository and reporting platform. This role ensures that the platform’s data, analytics, and integration architecture is leveraged to drive data into insights that drive business value using analytics, data visualization, and AI.
• The role acts as a solution architect and a technical authority for translating business and data requirements into robust architectural designs and ensuring architectural integrity across all releases. The role implements data ingestion pipelines, complex semantic models and delivers value driven visualizations and data outputs

Requirements

• Key Roles and Responsibilities: > Define and own the solution architecture for the semantic parts and use cases on the reporting platform, including data ingestion, transformation, semantic models, analytics, and consumption layers. > Design scalable and secure data architecture patterns aligned with the Global Data Platform and enterprise architecture standards. > Translate business and functional requirements into end-to-end technical designs, ensuring feasibility, performance, and maintainability. > Lead architectural decision-making for new capabilities, enhancements, and integrations, including trade-off analysis across cost, performance, and complexity. > Assess technical feasibility and lead proofs of concept (PoCs) for new requirements, technologies, and architectural patterns. > Collaborate closely with IT’s Data Foundation team to guide ETL implementation, ensuring adherence to agreed architectural designs. > Build semantic layers on top of DB/Datalake/Warhousing layers - Define and maintain architecture documentation, including logical, physical, and data flow diagrams. > Ensure robust data governance, security, and access control are embedded in the solution design. > Support user onboarding and adoption from a technical enablement perspective, ensuring solutions are intuitive, performant, and fit for purpose. > Provide architectural oversight for support, incidents, and enhancements, ensuring root causes are addressed structurally rather than tactically. KNOWLEDGE & ATTRIBUTES: > Advanced analytical mindset with the ability to structure ambiguous business problems, identify relevant data sources, and translate findings into clear, decision-ready insights. > Ability to translate complex business and functional requirements into clear, actionable technical designs across ingestion, transformation, semantic modelling, reporting, and consumption layers. > Strong understanding of business intelligence, data architecture, semantic modelling, data visualisation, and analytics delivery in enterprise environments. > Strong knowledge of data governance, data quality, data protection, privacy, security, and access control principles, with the judgement to embed them pragmatically into solution design. > Proficient in advanced analytics and reporting tools, including Excel, Power BI, SQL-based analysis, semantic models, DAX, and modern cloud data platform capabilities. > Strong ability to identify trends, anomalies, root causes, business opportunities, and risks from complex internal and external datasets. > Excellent communication, listening, interpersonal, and presentation skills, with the ability to explain technical topics to non-technical stakeholders and influence decisions across multiple teams. > Strong collaboration skills and ability to build trusted working relationships with business stakeholders, IT delivery teams, data governance, security, and platform teams. > High attention to detail, strong ownership mindset, and disciplined approach to documentation, requirements quality, testing, validation, and continuous improvement. > Self-directed, highly organised, outcome-oriented, and able to independently coordinate multiple assignments while maintaining delivery quality in a global, cross-functional environment. ACADEMIC QUALIFICATIONS & CERTIFICATIONS: Bachelor’s degree in a relevant discipline such as Computer Science, Information Systems, Data Analytics, Business Intelligence, Engineering, Mathematics, Statistics, Finance, Business Administration, or a related field. Advanced degree or postgraduate qualification in data, analytics, technology, or business is advantageous but not mandatory. Relevant professional certifications are advantageous, for example Microsoft Power BI Data Analyst, Microsoft Fabric, Azure Data Engineer, Azure Data Fundamentals, Databricks, SQL, data governance, data privacy, or agile delivery certifications. Equivalent combination of education, professional certifications, and demonstrable enterprise analytics experience may be considered. REQUIRED EXPERIENCE: > Advanced demonstrated experience working in a business intelligence, analytics, data product, or solution architecture capacity within a complex enterprise environment. > Proven experience translating business needs into end-to-end analytics solutions, including requirements definition, data sourcing, modelling, dashboard design, testing, deployment, and adoption support. > Advanced experience working with data collection, ingestion, transformation, validation, reconciliation, and reporting tools across internal and external data sources.
• > Strong hands-on experience with Power BI architecture, including report development, semantic models, DAX, performance optimisation, row-level security, deployment pipelines, and governed shared datasets.
• > Experience with modern data platforms and cloud-based analytics capabilities, such as Azure Data Factory, Microsoft Fabric, Databricks, SQL databases, data lakes, APIs, or comparable technologies.
• > Experience producing Excel-based and BI-based reporting, analytics outputs, briefing notes, dashboards, metrics layers, and executive-ready insights used to inform business decisions.
• > Demonstrated experience identifying trends, patterns, anomalies, business drivers, risks, and improvement opportunities from large or complex datasets. > Experience collaborating with business stakeholders, IT delivery teams, enterprise architecture, data governance, security, and privacy stakeholders to deliver secure, scalable, and maintainable analytics solutions. > Experience documenting requirements, specifications, data flows, business rules, metrics definitions, technical designs, testing outcomes, and operational support procedures. > Experience providing support, resolving business and data issues, recommending process improvements, and improving the accuracy, relevance, usability, and actionability of analytics outputs.