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Databricks Data Engineer Jobs in Nevada (NOW HIRING)

Data Strategy-Manager

Las Vegas, NV

$99K - $232K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... Databricks Certified Data Engineer / Data Analyst / ML - Proven leadership in data-driven strategies - Experience in defining data governance frameworks - Understanding of modern cloud data ...

Data Governance- Manager

Las Vegas, NV · On-site

$99K - $232K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... Databricks Certified Data Engineer / Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $99,000 - $232,000. Actual compensation within the ...

Data and Automation Engineer - Python

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

You'll work with modern technologies including Python, Databricks, and LLM-powered tools to build ... Strong Python programming skills with experience in data processing, automation, and API ...

Director, Data Architecture - Las Vegas, NV

Las Vegas, NV · Hybrid

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... Databricks and AWS. In this highly visible leadership role, you'll establish the standards, frameworks, and best practices that enable Data Engineering, Business Intelligence, and Data Science teams ...

Hands-on credibility in modern data infrastructure and data engineering, including cloud data platforms (Snowflake, Databricks, or equivalent), modern data tooling (dbt, MDM tooling), and ML platform ...

Hands-on credibility in modern data infrastructure and data engineering, including cloud data platforms (Snowflake, Databricks, or equivalent), modern data tooling (dbt, MDM tooling), and ML platform ...

Showing results 21-40

Databricks Data Engineer information

See Nevada salary details

$45.3K

$132.1K

$180.8K

How much do databricks data engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for databricks data engineer in Nevada is $132,091.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,600.00 and $140,000.00 per year, depending on experience, location, and employer.

What is a Databricks data engineer?

A Databricks Data Engineer is responsible for designing, building, and maintaining scalable data pipelines on the Databricks platform. They work with Apache Spark, Delta Lake, and cloud services to process large datasets efficiently. Their role involves data ingestion, transformation, optimization, and ensuring data quality for analytics and machine learning. Additionally, they collaborate with data scientists, analysts, and business teams to deliver reliable data solutions.

What does a Databricks data engineer do?

A typical day for a Databricks Data Engineer involves developing and maintaining scalable data pipelines, optimizing big data workflows using Spark, and collaborating with data scientists, analysts, and other engineers. You will regularly work within cloud environments to manage and process large datasets, conduct troubleshooting, and ensure data reliability and performance. Daily tasks may also include writing code, participating in team meetings, and implementing best practices for data security and governance. This role is highly collaborative, requiring frequent communication to align on project goals and address any technical challenges. The dynamic, project-based structure helps expand your skills and offers growth opportunities into senior engineering or data architecture roles.

What are the key skills and qualifications needed to thrive as a Databricks data engineer?

To thrive as a Databricks Data Engineer, you need strong expertise in data engineering concepts, big data processing, and programming languages such as Python, Scala, or SQL, often supported by a degree in computer science or a related field. Proficiency in Databricks, Apache Spark, cloud platforms (like AWS, Azure, or GCP), and relevant certifications such as Databricks Certified Data Engineer are highly valued. Effective problem-solving, collaboration, and clear communication skills help engineers work efficiently within cross-functional teams. These skills are essential for designing scalable data pipelines, ensuring data quality, and delivering actionable analytics in dynamic business environments.

How much does a Databricks data engineer make?

A Databricks Data Engineer typically earns between $90,000 and $150,000 annually, depending on experience, location, and certifications. Senior roles or those with advanced skills in Spark, cloud platforms, and data pipeline development can earn higher salaries.

Is a Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and big data processing. Skills in Apache Spark, cloud environments, and data pipeline development are highly sought after, leading to strong job growth in this field.

What are the most commonly searched types of Databricks Data Engineer jobs in Nevada?

The most popular types of Databricks Data Engineer jobs in Nevada are:

What are popular job titles related to Databricks Data Engineer jobs in Nevada?

For Databricks Data Engineer jobs in Nevada, the most frequently searched job titles are:

Infographic showing various Databricks Data Engineer job openings in Nevada as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $132,091 per year, or $63.5 per hour.

Lead Data Engineer - Delivery Lead

Purple Drive Technologies LLC

Las Vegas, NV • On-site

Other

Posted 21 days ago


Job description

About the job you're considering


The Delivery Lead will oversee the end-to-end delivery of a Teradata-to-Azure/Databricks migration powering client's next-generation curated analytics platform as well as coordinate delivery across other data-related initiatives. This role sits onsite in Las Vegas and requires strong leadership across gaming, hospitality, F&B, entertainment, digital, and enterprise analytics domains. The Delivery Lead will coordinate client delivery teams, client's business stakeholders, and technology partners to modernize the data ecosystem supporting, but not limited to, guest personalization, resort operations, gaming analytics, revenue optimization, and enterprise decisioning.

This is a high-visibility professional-services leadership role responsible for predictable delivery, stakeholder alignment, and ensuring client realizes measurable value from its cloud analytics transformation.

Your role
Delivery Leadership & Governance


Program Delivery Oversight - Lead multi-wave migration of Teradata workloads across gaming, loyalty, property operations, digital, F&B, entertainment, and enterprise analytics domains, along with other migration activities into EDH 2.0.
Governance & Reporting - Establish disciplined delivery governance aligned to client's PMO, including RAID management, executive status reporting, dependency tracking, and operational readiness checkpoints.
Stakeholder Management - Serve as a primary onsite interface for business and technology stakeholders, translating delivery progress, risks, and decisions into business-relevant language.
Risk & Issue Management - Proactively manage risks tied to high-traffic resort periods, major entertainment weekends, operational dependencies, data quality, platform readiness, and downstream analytics adoption.
Technical Program Leadership
EDH 2.0 Migration Strategy - Oversee migration planning and execution for enterprise data warehouse workloads, including Teradata tables, views, SQL logic, stored procedures, ETL/ELT dependencies, and analytics consumption patterns.
Azure Data Architecture - Guide delivery alignment to target-state Azure data architecture, including Azure Data Lake Storage, curated data zones, secure data-sharing patterns, and business-ready consumption layers.
Databricks Delivery - Ensure Azure Databricks pipelines, Delta Lake patterns, and medallion-oriented engineering practices support scalable analytics, reporting, personalization, forecasting, and enterprise decisioning use cases.
Data Analysis & Quality - Drive data profiling, reconciliation, validation, and KPI alignment across source and target platforms to support business confidence and production readiness.


Team, Financial & Partner Management


Onshore/Offshore Coordination - Manage client i delivery teams across architecture, data engineering, data analysis, QA, lineage, data modeling, and release coordination.
Resource Planning - Align capacity, skill mix, and work allocation to migration waves, delivery priorities, and business-domain sequencing.
Financial Governance - Support forecasting, burn tracking, scope management, and commercial discipline for a professional-services engagement.
Vendor & Partner Coordination - Coordinate effectively with Microsoft Azure, Databricks, client's technology partners, and other delivery stakeholders to remove blockers and maintain execution momentum.
Skills and experience
Teradata Modernization - High preference for leading or managing large Teradata modernization, migration, or decommissioning programs in complex enterprise environments.
Azure Data Platform - Strong working knowledge of Microsoft Azure data services, including Azure Data Lake Storage, secure cloud data patterns, orchestration, and enterprise-scale cloud migration practices.
Azure Databricks - Practical understanding of Azure Databricks, Spark-based engineering, Delta Lake, medallion architecture, and scalable data pipeline delivery.
SQL & Data Analysis - Strong SQL fluency and ability to guide teams through data profiling, mapping, reconciliation, transformation logic review, and issue resolution.
Data Architecture - Experience aligning migration delivery to target-state data architecture, curated analytics layers, semantic consumption patterns, governance expectations, and operational controls.
Complex Program Management - Experience leading large, multi-workstream delivery programs with onshore/offshore teams and multiple business and technology stakeholders.
Executive Communication - Skilled at presenting complex data and technology topics in clear, business-friendly language for senior client stakeholders.
Delivery Discipline - Strong ability to manage milestones, dependencies, risks, issues, scope, quality, release readiness, and operational transition.
Consulting Mindset - Ability to operate as a trusted professional-services leader focused on measurable outcomes, not solely staff augmentation or activity-based execution.
Domain Adaptability - Ability to quickly understand client's operating context across gaming, hospitality, F&B, entertainment, digital, and enterprise analytics domains.