1

Azure Data Platform Engineer Jobs in Nevada (NOW HIRING)

$61K - $141K/yr

You'll develop and deploy the pipelines and platforms that organize and make disparate data ... Experience with a public cloud, including AWS, Microsoft Azure, or Google Cloud * Experience with ...

Project - Data Engineer II

Las Vegas, NV · On-site

$109K - $131K/yr

... cloud platforms (AWS preferred; Azure/GCP acceptable). * Experience with data integration ... Knowledge of DevOps principles: CI/CD pipelines, version control, Infrastructure-as-Code. * Ability ...

Sr Data Engineer

Las Vegas, NV

$97K - $131K/yr

Senior Data Engineer Location: Las Vegas, NV Work Arrangement: 100% Onsite - 5 days per week ... Large-scale data initiatives (new source ingestion, platform expansion) * Real-time and streaming ...

This role is intentionally scoped as an Analytics Engineer, not just a data or platform engineer because success requires: * Understanding analytics use cases, business metrics, and performance KPIs

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

AI, ML & Agentic AI solutions, Establish reusable AI platforms, feature engineering frameworks, Drive adoption of Agentic AI workflows to automate data engineering, metadata management, testing ...

New

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

DevOps Engineer

Las Vegas, NV · On-site +1

$110K - $155K/yr

... Engineer who enjoys building, automating, and improving cloud infrastructure in a collaborative ... delivery, improve platform reliability, and drive automation across our Azure environment.

Showing results 41-60

Azure Data Platform Engineer information

What is the difference between Azure Data Platform Engineer vs Data Engineer?

AspectAzure Data Platform EngineerData Engineer
CertificationsAzure certifications (e.g., DP-203)General data engineering certifications (e.g., Google Cloud, AWS)
Work EnvironmentPrimarily cloud-based, Azure ecosystemOn-premises, cloud, or hybrid environments
Industry UsageOrganizations using Microsoft AzureVarious industries, broader data infrastructure roles
FocusDesigning, implementing, and managing Azure data solutionsBuilding and maintaining data pipelines and architectures

The Azure Data Platform Engineer specializes in Azure cloud data solutions, while the Data Engineer has a broader scope across different platforms and environments. Both roles require strong data management skills, but the Azure Data Platform Engineer focuses specifically on Azure services and certifications.

What are some common challenges Azure Data Platform Engineers face when integrating data from multiple sources?

Azure Data Platform Engineers often encounter challenges when consolidating data from diverse sources, such as differing data formats, inconsistent data quality, and varying update frequencies. Addressing these issues typically involves designing robust data pipelines using Azure Data Factory or Synapse, implementing effective data transformation and cleansing routines, and ensuring secure, compliant data movement. Collaborating closely with data architects and business analysts is essential to align technical solutions with organizational data governance and integration requirements.

What is an Azure Data Platform Engineer?

An Azure Data Platform Engineer is a technology professional who specializes in designing, building, and managing data solutions on Microsoft Azure. They work with services such as Azure SQL Database, Azure Data Factory, Azure Synapse Analytics, and other cloud-based data technologies to ensure efficient data storage, processing, integration, and analytics. Their role often involves implementing data pipelines, managing data security, optimizing performance, and supporting data-driven decision-making for organizations. Azure Data Platform Engineers typically collaborate with data scientists, analysts, and software developers to deliver robust and scalable data solutions.

What are the key skills and qualifications needed to thrive as an Azure Data Platform Engineer?

To thrive as an Azure Data Platform Engineer, you need expertise in data modeling, SQL, cloud architecture, and a strong understanding of Microsoft Azure services, typically supported by a degree in computer science or related fields. Familiarity with Azure Data Factory, Azure SQL Database, Databricks, and certifications like Microsoft Certified: Azure Data Engineer Associate are valuable. Strong analytical thinking, problem-solving skills, and effective communication set top performers apart in this role. These skills ensure the efficient design, deployment, and management of robust data solutions that support business intelligence and analytics needs.
What are popular job titles related to Azure Data Platform Engineer jobs in Nevada? For Azure Data Platform Engineer jobs in Nevada, the most frequently searched job titles are:

Forward Deployed Engineer, Microsoft AI & Data

Deloitte

Las Vegas, NV

$109K - $131K/yr

Other

Re-posted 18 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Microsoft AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

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.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Microsoft AI&Data including hands on experience with Azure AI Foundry.
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

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 $134,500 to $265,100.

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:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Recruiting for this role ends on 10/30/2026.

Work you'll do

As a Microsoft AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

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.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 3+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Microsoft AI&Data including hands on experience with Azure AI Foundry.
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

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 $134,500 to $265,100.

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:

What Deloitte employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom