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Job Description \#body.unify div.unify\-button\-container .unify\-apply\-now: focus, \#body.unify div.unify\-button\-container .unify\-apply\-\#body.unify div.unify\-button\-container .unify\-apply\-now: focus, \#body.unify div.unify\-button\-container .unify\-apply\-
Job Title: AI/Data Engineer
City: Minneapolis
State/Province: Minnesota
Posting Start Date: 7/17/26
Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future\-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever\-changing world. For additional information, visit us at www.wipro.com.
Job Description:
Job Description
Role Purpose
The purpose of the role is to liaison and bridging the gap between customer and Wipro delivery team to comprehend and analyze customer requirements and articulating aptly to delivery teams thereby, ensuring right solutioning to the customer.
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Do
1\. Customer requirements gathering and engagement
Interface and coordinate with client engagement partners to understand the RFP/ RFI requirements
Detail out scope documents, functional \& non\-functional requirements, features etc ensuring all stated and unstated customer needs are captured
Construct workflow charts and diagrams, studying system capabilities, writing specification after thorough research and analysis of customer requirements
Engage and interact with internal team \- project managers, pre\-sales team, tech leads, architects to design and formulate accurate and timely response to RFP/RFIs
Understand and communicate the financial and operational impact of any changes
Periodic cadence with customers to seek clarifications and feedback wrt solution proposed for a particular RFP/ RFI and accordingly instructing delivery team to make changes in the design
Empower the customers through demonstration and presentation of the proposed solution/ prototype
Maintain relationships with customers to optimize business integration and lead generation
Ensure ongoing reviews and feedback from customers to improve and deliver better value (services/ products) to the customers
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2\. Engage with delivery team to ensure right solution is proposed to the customer
a. Periodic cadence with delivery team to:
Provide them with customer feedback/ inputs on the proposed solution
Review the test cases to check 100% coverage of customer requirements
Conduct root cause analysis to understand the proposed solution/ demo/ prototype before sharing it with the customer
Deploy and facilitate new change requests to cater to customer needs and requirements
Support QA team with periodic testing to ensure solutions meet the needs of businesses by giving timely inputs/feedback
Conduct Integration Testing and User Acceptance demoâÃÂÃÂs testing to validate implemented solutions and ensure 100% success rate
Use data modelling practices to analyze the findings and design, develop improvements and changes
Ensure 100% utilization by studying systems capabilities and understanding business specifications
Stitch the entire response/ solution proposed to the RFP/ RFI before its presented to the customer
b. Support Project Manager/ Delivery Team in delivering the solution to the customer
Define and plan project milestones, phases and different elements involved in the project along with the principal consultant
Drive and challenge the presumptions of delivery teams on how will they successfully execute their plans
Ensure Customer Satisfaction through quality deliverable on time
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3\. Build domain expertise and contribute to knowledge repository
Engage and interact with other BAâÃÂÃÂs to share expertise and increase domain knowledge across the vertical
Write whitepapers/ research papers, point of views and share with the consulting community at large
Identify and create used cases for a different project/ account that can be brought at Wipro level for business enhancements
Conduct market research for content and development to provide latest inputs into the projects thereby ensuring customer delight
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Deliver
No. Performance Parameter Measure
1\. Customer Engagement and Delivery Management PCSAT, utilization % achievement, no. of leads generated from the business interaction, no. of errors/ gaps in documenting customer requirements, feedback from project manager, process flow diagrams (quality and timeliness), % of deal solutioning completed within timeline, velocity generated.
2\. Knowledge Management No. of whitepapers/ research papers written, no. of user stories created, % of proposal documentation completed and uploaded into knowledge repository, No of reusable components developed for proposal during quarter
Mandatory Skills: AI Cognitive .
Experience: 5\-8 Years .
The expected compensation for this role ranges from $60,000 to $135,000 .
Final compensation will depend on various factors, including your geographical location, minimum wage obligations, skills, and relevant experience. Based on the position, the role is also eligible for Wipro's standard benefits including a full range of medical and dental benefits options, disability insurance, paid time off (inclusive of sick leave), other paid and unpaid leave options.
Applicants are advised that employment in some roles may be conditioned on successful completion of a post\-offer drug screening, subject to applicable state law.
Wipro provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Applications from veterans and people with disabilities are explicitly welcome.
Reinvent your world. We are building a modern Wipro. We are an end\-to\-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA \- as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention.
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Salary Context
This $60K-$135K range is in the lower quartile for Data Engineer roles in our dataset (median: $150K across 15 roles with salary data).
Role Details
About This Role
Data Engineers build the pipelines that feed AI models. They design ETL workflows, manage data lakes, and ensure training and inference data is clean, timely, and accessible. Without good data engineering, AI projects fail. It's that simple.
The AI era has expanded the data engineer's scope far beyond batch ETL jobs. You're building real-time embedding pipelines for RAG systems, managing vector databases, ensuring training data quality at scale, and building the infrastructure that lets ML teams iterate on data as fast as they iterate on models. Data quality is the biggest predictor of model quality, and you're the person responsible for it.
Across the 3,708 AI roles we're tracking, Data Engineer positions make up 1% of the market. At Wipro, this role fits into their broader AI and engineering organization.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
What the Work Looks Like
A typical week includes: debugging a data pipeline that's producing stale embeddings for the RAG system, optimizing a Spark job that processes training data, building a data quality monitoring dashboard, meeting with the ML team to understand their next data requirements, and writing dbt models that transform raw event data into ML-ready features. The work is deeply technical and high-impact.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
Skills in Demand for This Role
SQL, Python, and distributed systems (Spark, Airflow, dbt) are core. Cloud data platforms (Snowflake, BigQuery, Redshift) are increasingly standard. Many AI-focused roles also want familiarity with vector databases and embedding pipelines. Understanding data modeling, pipeline orchestration, and data quality frameworks covers the essentials.
AI-specific data engineering skills include: building feature stores, managing training data versioning, implementing data lineage tracking, and building real-time embedding pipelines. Experience with streaming systems (Kafka, Flink) is valuable for real-time AI applications. Understanding ML data requirements (balanced datasets, data augmentation, evaluation set construction) makes you much more effective working with ML teams.
Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
Compensation Benchmarks
Data Engineer roles pay a median of $178,800 based on 40 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($97K) sits 45% below the category median. Disclosed range: $60K to $135K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Wipro AI Hiring
Wipro has 6 open AI roles right now. They're hiring across AI/ML Engineer, Data Engineer, Data Scientist, AI Software Engineer. Positions span Austin, TX, US, Minneapolis, MN, US, Jersey City, NJ, US. Compensation range: $121K - $158K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into Data Engineer roles include Backend Engineer, Database Administrator, Analytics Engineer.
From here, career progression typically leads toward Senior Data Engineer, ML Engineer, Data Platform Lead.
Master SQL and Python first. Then learn a distributed processing framework (Spark or its modern alternatives) and a pipeline orchestrator (Airflow, Dagster, Prefect). Build a portfolio project that demonstrates end-to-end pipeline construction: ingest, transform, validate, serve. If you want to specialize in AI data engineering, add vector databases and embedding pipelines to your skill set.
What to Expect in Interviews
Expect SQL deep-dives (query optimization, partitioning strategies, data modeling), Python coding focused on data pipeline patterns, and system design questions about building scalable ETL workflows. Companies with ML teams will ask about feature stores, embedding pipelines, and training data management. Be ready to discuss data quality monitoring, pipeline orchestration, and how you'd handle schema evolution in a production data lake.
When evaluating opportunities: Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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