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Reads like an Analytics Engineer role: dbt models and clean tables.
Mumbai, India
Live, first seen by us 36 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Define and own solution architecture for reporting platform use cases
Translate business requirements into end-to-end technical designs
Guide ETL implementation with IT's Data Foundation team
Build semantic layers on top of database, data lake and warehouse layers
Lead proofs of concept for new requirements and technologies
Define and own the solution architecture for the semantic parts and use cases on the reporting platform
Translate business and functional requirements into end-to-end technical designs
Collaborate closely with IT’s Data Foundation team to guide ETL implementation
Build semantic layers on top of DB/Datalake/Warhousing layers
Assess technical feasibility and lead proofs of concept (PoCs) for new requirements, technologies, and architectural patterns.
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.
As the third largest data center provider, we operate over 150 data centers in more than 20 countries and regions.
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Day 36
Similar jobs usually come down between day 6 and day 47.
From 1,409 similar postings that came down. Coming down is not always a hire.
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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.
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.
> 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.
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.
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Make an impact at NTT Global Data Centers
Join NTT Global Data Centers and be part of a team that drives innovation and sustainability in the digital world. With over 150 data centers across more than 20 countries globally, we offer unparalleled opportunities to work on cutting-edge technology and transformative projects. Experience a collaborative, innovative, and inclusive workplace where your ideas are valued, and your growth is supported.
Your role at a glance
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.What we are looking for
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.
Who we are
As the third largest data center provider, we operate over 150 data centers in more than 20 countries and regions. We understand that every business – large and small – has its own unique needs and goals. We offer local-to-global data center expertise, aligned with our connected platform of AI-ready data centers to create solutions that enable our clients to seamlessly scale their digital businesses, anywhere and anytime.
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Mumbai, India
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