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Entry Level Ai Data Engineer Jobs in Nevada (NOW HIRING)

AI Engineer

Las Vegas, NV · On-site

$55K - $187K/yr

Within our Internal Firm Services practice, you will apply data, algorithms, and software ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python ... Machine learning/AI candidates Ideal Candidates: Recent grads in CS, Engineering, Math, or ...

You'll build from the ground up: modernizing our data, developing our internal "company brain ... We're hiring our AI Solutions Engineer to lead that build: turning our internal knowledge and ...

You'll build from the ground up: modernizing our data, developing our internal "company brain ... We're hiring our AI Solutions Engineer to lead that build: turning our internal knowledge and ...

You'll build from the ground up: modernizing our data, developing our internal "company brain ... We're hiring our AI Solutions Engineer to lead that build: turning our internal knowledge and ...

The Quality Engineer, AI-Native is a core contributor on the quality engineering team, responsible ... Contribute to test data strategy for the squad's automated suites: design repeatable, isolated data ...

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Showing results 1-20

Entry Level Ai Data Engineer information

What are some common challenges faced by entry level AI data engineers in their first year on the job?

Entry level AI data engineers often encounter challenges such as learning to manage large datasets efficiently, understanding complex data pipelines, and adapting to rapidly evolving AI tools and frameworks. Collaborating with data scientists and senior engineers can be initially overwhelming, but it's a great opportunity to learn industry best practices. Balancing multiple tasks like data cleaning, preprocessing, and supporting model deployment while honing programming skills is typical. Proactively seeking feedback and asking questions is key to overcoming these hurdles and growing in the role.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior data scientists or AI research directors, which can offer compensation in that range including salary, bonuses, and stock options. Entry-level AI data engineering positions usually have lower salaries, but compensation can increase significantly with experience, skills, and responsibilities in the field.

What are the key skills and qualifications needed to thrive as an Entry Level AI Data Engineer, and why are they important?

To thrive as an Entry Level AI Data Engineer, you need proficiency in programming languages like Python or Java, a foundational understanding of data structures and algorithms, and a relevant degree in computer science or a related field. Familiarity with data processing frameworks (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure), and basic knowledge of machine learning libraries are typically expected. Strong analytical thinking, attention to detail, and effective teamwork set outstanding candidates apart. These skills and qualities are crucial for building reliable data pipelines, supporting AI models, and ensuring efficient collaboration within technical teams.

What is the difference between Entry Level Ai Data Engineer vs Data Analyst?

AspectEntry Level Ai Data EngineerData Analyst
Required SkillsBasic programming, data modeling, understanding of AI/ML conceptsData visualization, statistical analysis, SQL proficiency
CertificationsPython, SQL, entry-level AI/ML coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, AI startups, data-driven teamsBusiness, marketing, finance sectors
Job FocusBuilding AI models, data pipelines, integrating AI solutionsInterpreting data, creating reports, supporting decision-making

While both roles involve working with data, Entry Level Ai Data Engineers focus on developing AI models and data infrastructure, whereas Data Analysts primarily analyze data to generate insights. The former requires some knowledge of AI/ML, while the latter emphasizes statistical and visualization skills.

What engineer makes 500,000 a year?

Highly experienced senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn salaries approaching or exceeding $500,000 annually, especially with bonuses and stock options. These roles typically require advanced skills, extensive experience, and often work in high-demand industries like technology or finance.

How can I become an AI engineer with no experience?

To become an entry-level AI data engineer with no experience, focus on building foundational skills in programming languages like Python, learn about data management and machine learning concepts, and complete online courses or certifications in AI and data engineering. Gaining hands-on experience through personal projects, internships, or contributing to open-source initiatives can also help demonstrate your abilities to employers.

What is an Entry Level AI Data Engineer?

An Entry Level AI Data Engineer is a professional who helps build and maintain data pipelines and infrastructure to support artificial intelligence and machine learning applications. They typically work with large volumes of data, ensuring it is properly collected, cleaned, and organized for analysis. Their responsibilities may include working with databases, data processing tools, and cloud platforms, as well as collaborating with data scientists and software engineers to enable AI-driven solutions. This role is ideal for recent graduates or those new to the field, providing foundational experience in data engineering within the context of AI.

Which 3 jobs will survive AI?

Entry Level AI Data Engineers are likely to continue being in demand as they develop and maintain AI models, requiring skills in data management, programming, and machine learning tools. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as data scientists, AI specialists, and cybersecurity analysts, are also expected to persist despite AI automation. These roles often require specialized knowledge and adaptability that AI cannot fully replicate yet.
What are the most commonly searched types of Ai Data Engineer jobs in Nevada? The most popular types of Ai Data Engineer jobs in Nevada are:
What job categories do people searching Entry Level Ai Data Engineer jobs in Nevada look for? The top searched job categories for Entry Level Ai Data Engineer jobs in Nevada are:
What cities in Nevada are hiring for Entry Level Ai Data Engineer jobs? Cities in Nevada with the most Entry Level Ai Data Engineer job openings:
Infographic showing various Entry Level Ai Data Engineer job openings in Nevada as of July 2026, with employment types broken down into 71% Full Time, 20% Part Time, and 9% Contract. Highlights an 58% Physical, 3% Hybrid, and 39% Remote job distribution.

Data Engineer - Project Delivery Analyst

Deloitte

Las Vegas, NV • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 91 frontline employees who took The Breakroom Quiz

56th of 150 rated financial services


Job description

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Engineer - Project Delivery Analyst you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery.

Recruiting for this role ends on July 30th, 2026.

Work you'll do/Responsibilities  

You will support a Data & Analytics Foundry across numerous business product teams (scaled program with ~235 onshore/offshore resources), building reliable pipelines and curated datasets for analytics and downstream consumption.

  • Build and enhance data pipelines on AWS using Python to ingest, transform, and deliver data to Snowflake and downstream consumers.
  • Develop and maintain Snowflake objects (schemas, tables, views) and performant SQL transformations to produce curated, analytics-ready datasets.
  • Implement workflow automation and scheduling (e.g., Airflow/MWAA, Step Functions, Glue) with proper dependencies, retries, and logging.
  • Apply data quality checks and basic observability (validation rules, reconciliation, alerts) and support incident triage and remediation.
  • Optimize pipeline and query performance with guidance (efficient Python, partitioning/file formats in S3, Snowflake warehouse usage and query tuning).
  • Follow CI/CD and IaC standards (e.g., Git-based workflows, Terraform/CloudFormation changes) to promote code across environments.
  • Collaborate with analysts, product owners, and source-system teams to clarify requirements and validate outputs; participate in sprint ceremonies and estimations.
  • Contribute to code reviews (give/receive), unit tests, and peer debugging; learn and apply team engineering standards.
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

The Team 

AI& Data - AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Qualifications

Required

  • 1+ year of experience building/enhancing data pipelines and curated datasets for analytics/downstream consumers.
  • 1+ year of hands-on experience with SQL and Python, including Snowflake and/or PySpark for transformations and scalable processing.
  • 1+ year of experience with cloud data engineering on AWS (preferred) or Azure/GCP, including orchestration/scheduling (e.g., Airflow/MWAA, Step Functions, Glue, ADF/Fabric Data Factory).
  • Understanding of ELT patterns and Lakehouse/warehouse concepts; familiarity with S3 file formats/partitioning (e.g., Parquet/Delta).
  • Working knowledge of DevOps practices (Git-based workflows, CI/CD) and exposure to Infrastructure-as-Code (Terraform/CloudFormation).
  • Understanding data quality, basic observability, and metadata/governance fundamentals.
  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience.
  • Limited immigration sponsorship may be available.
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.

Preferred

  • Agile delivery experience .
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products.
  • Can operate independently or with minimum supervision.
  • Excellent written and communication skills.
  • Ability to deliver technical demonstrations.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $57,300 to $95,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Engineer - Project Delivery Analyst you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery.

Recruiting for this role ends on July 30th, 2026.

Work you'll do/Responsibilities  

You will support a Data & Analytics Foundry across numerous business product teams (scaled program with ~235 onshore/offshore resources), building reliable pipelines and curated datasets for analytics and downstream consumption.

  • Build and enhance data pipelines on AWS using Python to ingest, transform, and deliver data to Snowflake and downstream consumers.
  • Develop and maintain Snowflake objects (schemas, tables, views) and performant SQL transformations to produce curated, analytics-ready datasets.
  • Implement workflow automation and scheduling (e.g., Airflow/MWAA, Step Functions, Glue) with proper dependencies, retries, and logging.
  • Apply data quality checks and basic observability (validation rules, reconciliation, alerts) and support incident triage and remediation.
  • Optimize pipeline and query performance with guidance (efficient Python, partitioning/file formats in S3, Snowflake warehouse usage and query tuning).
  • Follow CI/CD and IaC standards (e.g., Git-based workflows, Terraform/CloudFormation changes) to promote code across environments.
  • Collaborate with analysts, product owners, and source-system teams to clarify requirements and validate outputs; participate in sprint ceremonies and estimations.
  • Contribute to code reviews (give/receive), unit tests, and peer debugging; learn and apply team engineering standards.
  • Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
  • Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

The Team 

AI& Data - AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Qualifications

Required

  • 1+ year of experience building/enhancing data pipelines and curated datasets for analytics/downstream consumers.
  • 1+ year of hands-on experience with SQL and Python, including Snowflake and/or PySpark for transformations and scalable processing.
  • 1+ year of experience with cloud data engineering on AWS (preferred) or Azure/GCP, including orchestration/scheduling (e.g., Airflow/MWAA, Step Functions, Glue, ADF/Fabric Data Factory).
  • Understanding of ELT patterns and Lakehouse/warehouse concepts; familiarity with S3 file formats/partitioning (e.g., Parquet/Delta).
  • Working knowledge of DevOps practices (Git-based workflows, CI/CD) and exposure to Infrastructure-as-Code (Terraform/CloudFormation).
  • Understanding data quality, basic observability, and metadata/governance fundamentals.
  • Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience.
  • Limited immigration sponsorship may be available.
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve.

Preferred

  • Agile delivery experience .
  • Analytical ability to manage multiple projects and prioritize tasks into manageable work products.
  • Can operate independently or with minimum supervision.
  • Excellent written and communication skills.
  • Ability to deliver technical demonstrations.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $57,300 to $95,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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