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Deloitte Data Analytics Jobs in Nevada (NOW HIRING)

Project - Data Engineer II

Las Vegas, NV

$109K - $131K/yr

If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project ... Work you'll do/Responsibilities As part of the Data & Analytics Foundry you will support numerous ...

SAP BODS/Data Conversion Consultant

Las Vegas, NV · On-site

$63.75 - $83/hr

Our Deloitte Enterprise Performance team is at the forefront of enterprise technology, working ... analysis for master and transactional data to improve data quality and reduce conversion risk.

If so, consider an opportunity with Deloitte under our Project Talent Model. Project Talent Model ... software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by ...

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Showing results 1-20

Deloitte Data Analytics information

See Nevada salary details

$46.8K

$168K

$248K

How much do deloitte data analytics jobs pay per year?

As of Jul 30, 2026, the average yearly pay for deloitte data analytics in Nevada is $168,039.00, according to ZipRecruiter salary data. Most workers in this role earn between $135,900.00 and $173,100.00 per year, depending on experience, location, and employer.

What is the difference between Deloitte Data Analytics vs Data Analyst?

AspectDeloitte Data AnalyticsData Analyst
Required CredentialsBachelor's degree in related field, certifications like Tableau, Power BI, or SQL often preferredBachelor's degree in data-related field; certifications are a plus but not mandatory
Work EnvironmentConsulting firm environment, client-facing projects, collaborative teamsCorporate or organizational setting, focus on internal data analysis
Employer & Industry UsageUsed by Deloitte in consulting and advisory services across industriesCommon in various industries for internal data reporting and analysis

While Deloitte Data Analytics involves working within a consulting firm to deliver data-driven solutions to clients, Data Analysts typically focus on analyzing internal company data to support decision-making. Both roles require similar skills and certifications, but Deloitte Data Analytics often involves client interaction and project management in a consulting context.

What does a Deloitte Data Analytics professional do?

A Deloitte Data Analytics professional leverages data analysis tools and techniques to help clients make informed business decisions. Their responsibilities include collecting, processing, and interpreting large sets of data to uncover trends and insights. They work with advanced analytics, machine learning, and data visualization to solve complex business challenges across various industries. By turning raw data into actionable information, Deloitte Data Analytics professionals drive strategic growth and operational efficiency for their clients.

What are some common challenges faced by data analytics professionals at Deloitte, and how are they typically addressed?

Data analytics professionals at Deloitte often encounter challenges such as working with large, complex datasets from diverse sources and ensuring data quality and integrity. Client expectations can also add pressure to deliver actionable insights within tight deadlines. To address these challenges, teams at Deloitte emphasize collaborative problem-solving, leverage advanced analytical tools, and follow strict data governance protocols. Ongoing training and support from experienced colleagues help team members continuously improve their technical and communication skills.

What are the key skills and qualifications needed to thrive as a Data Analytics professional at Deloitte, and why are they important?

To thrive as a Data Analytics professional at Deloitte, you need strong analytical skills, proficiency in statistics, and a solid educational background in fields like mathematics, computer science, or engineering. Familiarity with data analytics tools such as SQL, Python, R, Tableau, and relevant certifications like Certified Analytics Professional (CAP) are highly valuable. Exceptional problem-solving, communication, and teamwork abilities help you interpret data insights and collaborate with clients and colleagues. These skills ensure you can deliver data-driven solutions that support business decision-making and drive client success.
What are the most commonly searched types of Deloitte Data Analytics jobs in Nevada? The most popular types of Deloitte Data Analytics jobs in Nevada are:
What are popular job titles related to Deloitte Data Analytics jobs in Nevada? For Deloitte Data Analytics jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Deloitte Data Analytics jobs in Nevada look for? The top searched job categories for Deloitte Data Analytics jobs in Nevada are:
What cities in Nevada are hiring for Deloitte Data Analytics jobs? Cities in Nevada with the most Deloitte Data Analytics job openings:
Infographic showing various Deloitte Data Analytics job openings in Nevada as of July 2026, with employment types broken down into 1% Internship, 93% Full Time, 3% Part Time, and 3% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $168,039 per year, or $80.8 per hour.

Data Engineer - Project Delivery Analyst

Deloitte

Las Vegas, NV • On-site

Other

Re-posted 10 days ago


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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