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Architect - Advanced Analytics

Hyderabad, Telangana, India

Live, first seen by us 23 days ago
Pay
Pay not listed
Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid remote
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll bring

All qualifications

Core experience

  • Ability to manage competing priorities, collaborate across cross-functional teams, and consistently deliver results in a fast-paced, performance-driven setting.
Qualification wording
· Proven success operating within large, matrixed consulting organizations and navigating the scale, complexity, governance, and pace of a Global System Integrator (GSI) environment. Ability to manage competing priorities, collaborate across cross-functional teams, and consistently deliver results in a fast-paced, performance-driven setting.
Apply at Cognizant

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Status in our records
Live
First seen by us
Oct 21, 202623 days ago
Recorded sightings
44
Last seen by us
Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 23

Similar jobs usually come down between day 4 and day 77.

At Cognizant, jobs usually come down by about day 23.

From 51 similar postings that came down, and 425 of Cognizant’s. Coming down is not always a hire.

Cognizant is hiring

136 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 4% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • R
  • SQL
  • Azure
  • Databricks
  • Delta Lake
  • Power BI
  • Power Query
Where the posting names them
· Power BI tenant and workspace management to support development, testing and deployment. · Experience with analytics and custom visualizations for Power BI using Python, R. · Strong SQL skills and experience optimizing analytical queries.
· Power BI Service administration and deployment pipelines. · Deploying cloud-based solutions using Microsoft Azure data services including Azure Data Factory, Azure Data Lake, and Azure SQL DB. · Power BI tenant and workspace management to support development, testing and deployment.
· Experience with analytics and custom visualizations for Power BI using Python, R. · Strong SQL skills and experience optimizing analytical queries. · Working familiarity with LLMs, AI-augmented analytics workflows, and Model Context Protocol (MCP) tooling, and how they expand traditional BI into how people interact with data.
Shift: Flexible to work in Shifts The Architect in Delivery is a hands-on technical lead for cloud solutions. You design and deliver secure, scalable, and maintainable systems on Azure that solve real business problems. You own end-to-end architecture for your projects, stay close to implementation where it matters, and work with teams to meet goals for value, security, performance, reliability, and cost. Our Advanced Analytics practice improves decision-making through consistent, trusted analytics across four pillars—conversational analytics, decision agents, BI & dashboarding, and semantic modelling—and you architect solutions across all four as decision-intelligence systems—spanning data → signal → decision → action → learning—so analytics becomes the operational front door, not a downstream report. At this level, you lead solution design in your primary domain, guide engineers day to day, and mentor other architects and technical leads. You turn business needs into clear technical plans, help teams make good tradeoffs, and keep delivery predictable and high quality.
Solution Architecture and Technical Leadership · Own end-to-end architecture and scope for your projects, leading teams to design and deliver Azure solutions that meet agreed goals for value, security, scalability, reliability, performance, and cost. · Serve as the technical lead and subject matter expert on your engagements, guiding consultants and engineers so implementation stays aligned with the architecture and standards.
· Proven experience leading hybrid and remote teams and maintaining alignment, quality, and predictable delivery across time zones. · Expertise in at least one major public cloud platform, with Azure strongly preferred. · Deep understanding of core concepts, languages, frameworks, and design patterns in your primary domain, with the ability to apply them to build robust, maintainable systems.
· Use AI tools to accelerate code, tests, documentation, and similar tasks, and share effective practices so they become repeatable gains for teams and clients. · Design end-to-end analytics architecture spanning ingestion, lakehouse, semantic layer, and consumption—including a conversational/agent layer built on Microsoft Fabric data agents and Databricks Genie. · Advise clients on Power BI / Microsoft Fabric architecture, governance, capacity, and deployment strategy.
· Embed AI-augmented and agentic capabilities—LLMs grounded on governed semantic models via Model Context Protocol (MCP)—and intelligent decision systems into solution designs. · Architect end-to-end decision-intelligence systems across the data → signal → decision → action → learning stack—OneLake/Lakehouse and Databricks, AI-ready semantic/knowledge models, Fabric data agents and Databricks Genie, translytical task flows, and AI-augmented decision workflows. · Design the agent, write-back, and human-in-the-loop governance layers so analytics drives action directly rather than handing off to a separate operational system.
· Experience using AI-augmented development and integrating AI or machine learning capabilities into solutions through APIs, libraries, or cloud-based AI services. · Hands-on experience with Microsoft Fabric (OneLake, Lakehouse, Direct Lake, Dataflows Gen2, data agents) and/or Databricks (Delta, Unity Catalog, Genie). · Experience working in Agile or Scrum environments, including backlog refinement and iteration planning.
· Design end-to-end analytics architecture spanning ingestion, lakehouse, semantic layer, and consumption—including a conversational/agent layer built on Microsoft Fabric data agents and Databricks Genie. · Advise clients on Power BI / Microsoft Fabric architecture, governance, capacity, and deployment strategy. · Embed AI-augmented and agentic capabilities—LLMs grounded on governed semantic models via Model Context Protocol (MCP)—and intelligent decision systems into solution designs.
· 7+ years of experience in business intelligence, analytics, or 5+ in consulting. · Deep expertise in Power BI, including: · Enterprise report and dashboard design.
· Advanced DAX, Power Query/M skills, and performance optimization experience. · Power BI Service administration and deployment pipelines. · Deploying cloud-based solutions using Microsoft Azure data services including Azure Data Factory, Azure Data Lake, and Azure SQL DB.
· Deploying cloud-based solutions using Microsoft Azure data services including Azure Data Factory, Azure Data Lake, and Azure SQL DB. · Power BI tenant and workspace management to support development, testing and deployment. · Experience with analytics and custom visualizations for Power BI using Python, R.
· Enterprise report and dashboard design. · Advanced DAX, Power Query/M skills, and performance optimization experience. · Power BI Service administration and deployment pipelines.

Your next step

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About Cognizant

People
About 351,600 in 2025, up 4% from the year before.Annual report (SEC Form 10-K)
Company
Listed as CTSH.
H-1B visas
1,401 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for AI Engineer roles

New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.

Weekly new AI Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 7, the most 65, and the latest week had 65.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under AI Engineer, by the work the posting describes.

AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.

Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.

An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.

Job description

View original posting ↗

Skill: Architect - Advanced Analytics

Exp: 9 to 13 years

Location: Hyderabad

Shift: Flexible to work in Shifts

The Architect in Delivery is a hands-on technical lead for cloud solutions. You design and deliver secure, scalable, and maintainable systems on Azure that solve real business problems. You own end-to-end architecture for your projects, stay close to implementation where it matters, and work with teams to meet goals for value, security, performance, reliability, and cost. Our Advanced Analytics practice improves decision-making through consistent, trusted analytics across four pillars—conversational analytics, decision agents, BI & dashboarding, and semantic modelling—and you architect solutions across all four as decision-intelligence systems—spanning data → signal → decision → action → learning—so analytics becomes the operational front door, not a downstream report.

At this level, you lead solution design in your primary domain, guide engineers day to day, and mentor other architects and technical leads. You turn business needs into clear technical plans, help teams make good tradeoffs, and keep delivery predictable and high quality.

Responsibilities

Solution Architecture and Technical Leadership

· Own end-to-end architecture and scope for your projects, leading teams to design and deliver Azure solutions that meet agreed goals for value, security, scalability, reliability, performance, and cost.

· Serve as the technical lead and subject matter expert on your engagements, guiding consultants and engineers so implementation stays aligned with the architecture and standards.

· Apply sound engineering practices—clear interfaces, modular design, and testability—to produce reliable, maintainable solutions in your primary domain.

· Provide architectural guidance throughout implementation, including design and pull-request reviews, shaping cloud patterns and guardrails and offering practical options to unblock teams.

· Use AI tools to accelerate code, tests, documentation, and similar tasks, and share effective practices so they become repeatable gains for teams and clients.

· Design end-to-end analytics architecture spanning ingestion, lakehouse, semantic layer, and consumption—including a conversational/agent layer built on Microsoft Fabric data agents and Databricks Genie.

· Advise clients on Power BI / Microsoft Fabric architecture, governance, capacity, and deployment strategy.

· Embed AI-augmented and agentic capabilities—LLMs grounded on governed semantic models via Model Context Protocol (MCP)—and intelligent decision systems into solution designs.

· Architect end-to-end decision-intelligence systems across the data → signal → decision → action → learning stack—OneLake/Lakehouse and Databricks, AI-ready semantic/knowledge models, Fabric data agents and Databricks Genie, translytical task flows, and AI-augmented decision workflows.

· Design the agent, write-back, and human-in-the-loop governance layers so analytics drives action directly rather than handing off to a separate operational system.

· Delivery and Consulting Excellence

· Lead discovery and requirements sessions for your workstreams, clarifying scope, dependencies, and risks, and shaping a prioritized backlog with clear acceptance criteria tied to business outcomes.

· Explain complex technical topics in simple, direct language for both technical and non-technical audiences, and consistently connect technical decisions back to client goals.

· Build trust with managers and product owners, influencing priorities and roadmaps in ways that support the client’s long-term interests.

· Enable teams to deliver with stable velocity and low defect rates by providing clear architecture, interfaces, and automation across build, test, and deployment, and by designing for incremental delivery with a clear Definition of Done.

· Align multiple teams on shared outcomes, contracts, and integration points, ensuring dependencies are identified early, owned, and tracked through delivery.

· Support effective Agile practices by ensuring the architecture and backlog structure enable incremental delivery, a clear Definition of Done, and data-informed course corrections based on telemetry and feedback.

· Mentorship and Team Development

· Mentor others through pairing, design reviews, and clear feedback that strengthens design skills, technical judgment, and confidence, with a particular focus on senior engineers and technical leads.

· Provide architectural oversight across teams or workstreams, modeling pragmatic decision-making and teaching others when to keep designs simple and when to introduce new patterns or technologies.

· Support hiring and growth by participating in technical interviews, calibration discussions, and cross-project mentorship.

· Growth and Innovation

· Contribute to business development by identifying opportunities across all our capabilities (beyond own specialty) and communicating them to the sales director.

· Partner with sales and account leaders on pursuits by defining the cloud vision, contributing architectural viewpoints, and participating in client workshops, demos, and roadmap discussions.

· Produce solution options, high-level designs, and estimates in your domains, clearly documenting assumptions, dependencies, and risks and explaining how proposed approaches drive business value and reduce risk.

· Create and maintain reusable assets—such as runbooks, workshops, starter repositories, and templates—that make it easier for engineers to deliver consistent solutions.

· Champion modern frameworks, patterns, tools, and AI-assisted practices that improve quality, speed, or reliability in a secure and responsible way.

· Actively participate in enablement efforts that support a culture of collaboration, continuous improvement, and knowledge sharing

Requirements

· 6+ years of experience delivering solutions in a primary domain such as application development, cloud platform engineering, DevOps, or data and analytics.

· 3+ years of experience in solution architecture and leading development or engineering teams.

· 7+ years of experience in business intelligence, analytics, or 5+ in consulting.

· Deep expertise in Power BI, including:

· Enterprise report and dashboard design.

· Advanced DAX, Power Query/M skills, and performance optimization experience.

· Power BI Service administration and deployment pipelines.

· Deploying cloud-based solutions using Microsoft Azure data services including Azure Data Factory, Azure Data Lake, and Azure SQL DB.

· Power BI tenant and workspace management to support development, testing and deployment.

· Experience with analytics and custom visualizations for Power BI using Python, R.

· Strong SQL skills and experience optimizing analytical queries.

· Working familiarity with LLMs, AI-augmented analytics workflows, and Model Context Protocol (MCP) tooling, and how they expand traditional BI into how people interact with data.

· Proven experience architecting decision-intelligence solutions—AI-ready semantic/knowledge models, Fabric data agents, translytical task flows, and AI-augmented decision workflows.

· Proven experience leading hybrid and remote teams and maintaining alignment, quality, and predictable delivery across time zones.

· Expertise in at least one major public cloud platform, with Azure strongly preferred.

· Deep understanding of core concepts, languages, frameworks, and design patterns in your primary domain, with the ability to apply them to build robust, maintainable systems.

· Experience using AI-augmented development and integrating AI or machine learning capabilities into solutions through APIs, libraries, or cloud-based AI services.

· Hands-on experience with Microsoft Fabric (OneLake, Lakehouse, Direct Lake, Dataflows Gen2, data agents) and/or Databricks (Delta, Unity Catalog, Genie).

· Experience working in Agile or Scrum environments, including backlog refinement and iteration planning.

· Experience in consulting or professional services is a plus.

· Familiarity with key cloud services for your domain, such as messaging, compute, data, security, networking, and integration.

· Strong analytical and problem-solving skills, with clear written and verbal communication.

· Demonstrated interest in continuous learning and adoption of new cloud technologies.

· Ability to be hands-on with implementation while also designing and communicating complex cloud architectures.

· Proven success operating within large, matrixed consulting organizations and navigating the scale, complexity, governance, and pace of a Global System Integrator (GSI) environment. Ability to manage competing priorities, collaborate across cross-functional teams, and consistently deliver results in a fast-paced, performance-driven setting.

Source details

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Location & working pattern

Hyderabad, Telangana, India

· Proven experience architecting decision-intelligence solutions—AI-ready semantic/knowledge models, Fabric data agents, translytical task flows, and AI-augmented decision workflows. · Proven experience leading hybrid and remote teams and maintaining alignment, quality, and predictable delivery across time zones. · Expertise in at least one major public cloud platform, with Azure strongly preferred.
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