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Data Engineer Gcp Data Engineer Jobs in Nevada (NOW HIRING)

Programmers.io

Technical Program Manager

Las Vegas, NV · On-site

$123K - $159K/yr

CI/CD (Azure DevOps/GitHub Actions/Jenkins). * Data warehousing/lakehouse patterns; batch & streaming (e.g., Structured Streaming). Cloud (one or more) * Azure (preferred), AWS, or GCP --including ...

Deloitte

Lead Forward Deployed Engineer - AWS

Las Vegas, NV · On-site

$97K - $128K/yr

Work you'll do As an AWS AI&Data FDE, you will work side by side with senior functional and ... Solution Engineering * Build AI-enabled solutions, agentic platforms, and workflows across ...

Lnw

Head of Data

Las Vegas, NV

Stand up L&W's centralized data hub, including infrastructure, master data management, governance, data engineering, analytics engineering, and data science capability. * Define and operate the hub ...

Light and Wonder, Inc.

Head of Data

Las Vegas, NV · On-site

Stand up L&W's centralized data hub, including infrastructure, master data management, governance, data engineering, analytics engineering, and data science capability. * Define and operate the hub ...

Pwc

AI & GenAI Data Scientist - Manager

Las Vegas, NV

$99K - $232K/yr

In this role at PwC, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based ...

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All JobsData Engineer Gcp Data Engineer JobsData Engineer Gcp Data Engineer Jobs in Nevada

Data Engineer Gcp Data Engineer information

What is a GCP data engineer?

A GCP Data Engineer is a data engineering professional who specializes in designing, building, and managing data processing systems on Google Cloud Platform (GCP). They work with cloud-based tools and services to collect, transform, and analyze large volumes of data, enabling organizations to gain insights and make data-driven decisions. GCP Data Engineers are proficient in technologies such as BigQuery, Dataflow, Pub/Sub, and Cloud Storage. Their role often involves ensuring data pipelines are reliable, scalable, and secure while optimizing performance and cost.

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

To thrive as a GCP Data Engineer, you need strong expertise in data modeling, ETL processes, and cloud architecture, typically backed by a degree in computer science or related field. Proficiency with Google Cloud Platform services (like BigQuery, Dataflow, and Pub/Sub), SQL, and tools such as Python or Java is essential, and certifications like Google Professional Data Engineer are highly valued. Strong problem-solving, communication, and teamwork skills help you collaborate effectively and translate business needs into technical solutions. These abilities ensure efficient, scalable data pipelines and reliable infrastructure, which are critical for driving data-driven decision-making.

What are some common challenges faced by data engineers working with GCP, and how can they be addressed?

Data Engineers working with Google Cloud Platform (GCP) often encounter challenges such as optimizing data pipeline performance, managing costs, and ensuring data security and compliance. Effective use of GCP's native monitoring and logging tools can help identify bottlenecks in ETL processes, while leveraging features like autoscaling in Dataflow or BigQuery partitioning improves efficiency. Regular collaboration with DevOps and security teams is crucial to maintain robust cloud architecture and compliance with data regulations. Staying updated with GCP releases and best practices will also help proactively address evolving challenges.

What is the difference between Data Engineer Gcp Data Engineer vs Data Engineer?

AspectData Engineer Gcp Data EngineerData Engineer
CertificationsGCP certifications (e.g., Professional Data Engineer)Varies; often includes cloud or database certifications
Work EnvironmentPrimarily cloud-based, focusing on Google Cloud Platform toolsCan be cloud, on-premises, or hybrid environments
Industry UsageCommon in organizations leveraging Google Cloud servicesWidespread across industries using various cloud providers
Skills FocusGCP tools, BigQuery, Dataflow, Pub/SubSQL, ETL, data modeling, general cloud skills

In summary, Data Engineer Gcp Data Engineer specializes in Google Cloud Platform tools and certifications, focusing on cloud-native data solutions. Data Engineer is a broader role that may work across multiple platforms and environments, with a wider range of tools and technologies.

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

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

What job categories do people searching Data Engineer Gcp Data Engineer jobs in Nevada look for?

The top searched job categories for Data Engineer Gcp Data Engineer jobs in Nevada are:

What cities in Nevada are hiring for Data Engineer Gcp Data Engineer jobs?

Cities in Nevada with the most Data Engineer Gcp Data Engineer job openings:

Data Engineer Gcp Data Engineer jobs near you
Infographic showing various Data Engineer Gcp Data Engineer job openings in Nevada as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Technical Program Manager

Programmers.io

Las Vegas, NV • On-site

$123K - $159K/yr

Full-time

Re-posted 16 days ago

Job description

Role Summary

We are seeking a senior Technical Program Manager to lead complex, multi‑workstream data platform initiatives using Databricks and modern ETL/ELT patterns. The TPM will drive strategy, delivery, and governance across data engineering, analytics, and platform modernization efforts—managing roadmaps, budgets, risks, and stakeholder communication while enabling high-performing teams to deliver business value at scale.

Key Responsibilities

Program Leadership & Strategy

  • Own end‑to‑end program strategy, roadmap, and execution for Databricks‑centric data platform initiatives.
  • Translate business outcomes into measurable OKRs/KPIs and delivery milestones.
  • Orchestrate cross‑functional delivery across data engineering, platform, DevOps, QA, and security teams.

Delivery Management

  • Establish delivery governance (RAID, change control, dependencies, risk burndown) and ensure on‑time, on‑budget delivery.
  • Drive Agile at scale (Scrum/Kanban/SAFe), sprint health, throughput, and release management.
  • Define and enforce SLAs/SLOs for data pipelines, batch/streaming jobs, and analytics products.

Technical Program Ownership (Databricks/ETL)

  • Guide solution direction for Databricks (Apache Spark, Delta Lake, Unity Catalog), ETL/ELT flows, and data warehousing.
  • Oversee modernization/migration programs (onprem to cloud), cost optimization (cluster policies, job scheduling), and performance tuning.
  • Ensure robust CI/CD for data pipelines, IaC for platform components, and environment parity across Dev/Test/Prod.

Data Architecture & Governance

  • Partner with architects on data models, lakehouse patterns, CDC, and medallion architecture.
  • Implement data quality, lineage, cataloging, and access controls (e.g., Unity Catalog, row/column-level security).
  • Ensure compliance with data privacy and regulatory requirements (e.g., PII/GDPR as applicable).

Stakeholder & Customer Management

  • Engage senior business stakeholders, product owners, and client leadership; manage expectations and executive reporting.
  • Convert ambiguous requirements into clear program epics with acceptance criteria and success measures.
  • Lead partner/vendor engagements, SOWs, and third‑party delivery alignment.

People Leadership

  • Build and mentor high-performing teams (engineering managers, data engineers, analysts, QA).
  • Lead hiring, capacity planning, performance management, and career development.
  • Promote engineering excellence, documentation discipline, and a culture of continuous improvement.

Financials & Commercials

  • Own program budgets, resource plans, and cost controls (cloud/Databricks spend).
  • Track and report financials: forecasts, burn rates, and variance analysis.
  • Support proposals, estimations, and SOW renewals/extensions.

Must‑Have Skills

Program Management

  • Enterprise-scale program ownership, governance, RAID management, executive communication.
  • Strong backlog management, prioritization, and stakeholder alignment.
  • Proven delivery of multi‑workstream, multi‑vendor programs.

Databricks & Data Engineering

  • Databricks (Spark, Delta Lake, Unity Catalog, Job clusters), performance tuning & cost governance.
  • ETL/ELT using Azure Data Factory / Synapse Pipelines / dbt / Airflow / Informatica (any strong combo).
  • Strong SQL & practical Python for data workflows; CI/CD (Azure DevOps/GitHub Actions/Jenkins).
  • Data warehousing/lakehouse patterns; batch & streaming (e.g., Structured Streaming).

Cloud (one or more)

  • Azure (preferred), AWS, or GCP—including storage, compute, IAM, networking basics, and monitoring.

Data Governance & Quality

  • Data cataloging/lineage, DQ frameworks, access control, secrets management, auditability.

Leadership & Communication

  • Team leadership (15–40 members), mentorship, and conflict resolution.
  • Clear, concise communication with senior business and technical audiences.

Good‑to‑Have

  • Certifications: PMP/Prince2, SAFe/CSM, Databricks Data Engineer Professional, Azure/AWS cloud certs.
  • Tools: Terraform/Bicep, Datadog/CloudWatch/Log Analytics, Great Expectations, Monte Carlo, Collibra/Purview.
  • Domain exposure: Media/Entertainment, Telecom, BFSI, or Retail/E‑commerce.

Education

  • Bachelor’s or Master’s in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).