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Manager Data Analytics Engineer Jobs in Nevada (NOW HIRING)

You will collaborate closely with Data Engineering, who manage the source-to-mesh pipelines, and build everything needed to deliver clean, reliable, analytics-ready data into the BI workspace. This ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary The Opportunity As a Data Engineer - Manager, you will play a pivotal role in transforming raw data ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate & Summary The Opportunity As a Data Engineer - Senior Associate, you will focus on designing and ...

Data Analyst

Las Vegas, NV · On-site

$25 - $35/hr

Responsibilities: o Perform data processing tasks and prepare data analytics reports meeting ... management and engineering consulting company serving the electric utilities industry.

Data Analyst

Las Vegas, NV · On-site

$25 - $35/hr

Responsibilities: o Perform data processing tasks and prepare data analytics reports meeting ... management and engineering consulting company serving the electric utilities industry.

You'll assist in evaluating interconnection options, analyzing project feasibility, preparing ... Bachelor's degree in engineering, applied science, economics, or related discipline. * Familiarity ...

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Manager Data Analytics Engineer information

What is the difference between Manager Data Analytics Engineer vs Data Analytics Engineer?

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

How does a Manager Data Analytics Engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

What are the key skills and qualifications needed to thrive as a Manager Data Analytics Engineer, and why are they important?

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is a Manager Data Analytics Engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.
What are the most commonly searched types of Data Analytics Engineer jobs in Nevada? The most popular types of Data Analytics Engineer jobs in Nevada are:
What are popular job titles related to Manager Data Analytics Engineer jobs in Nevada? For Manager Data Analytics Engineer jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Manager Data Analytics Engineer jobs in Nevada look for? The top searched job categories for Manager Data Analytics Engineer jobs in Nevada are:
What cities in Nevada are hiring for Manager Data Analytics Engineer jobs? Cities in Nevada with the most Manager Data Analytics Engineer job openings:
Analytics Engineer

Analytics Engineer

Socure

Carson City, NV

Full-time

Posted 7 days ago


Job description

Why Socure?

Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.

We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.

About the Role

We are looking for an experienced Analytics Engineer to own and evolve the BI team’s technical infrastructure (Snowflake, dbt, GitLab CI/CD, scheduling frameworks, and ingestion tooling) while ensuring all BI systems and workflows remain fully aligned with the broader Data Engineering architecture and design principles. This role is responsible for keeping the BI environment scalable, maintainable, and consistent with the company’s overall data platform strategy.

You will collaborate closely with Data Engineering, who manage the source-to-mesh pipelines, and build everything needed to deliver clean, reliable, analytics-ready data into the BI workspace. This includes developing curated data layers, ensuring pipeline reliability, maintaining governance standards, and enabling efficient downstream analytics across dashboards, reporting, and domain models.

Why “Analytics” Engineer?

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

  • Designing data models that correctly support those metrics and semantic definitions
    Working closely with business stakeholders to gather context and ensure data structures reflect real-world logic

  • Balancing technical efficiency with analytical usability, building data assets that analysts and business teams can reliably use for decision-making

You will serve as the bridge between technical data systems and the analytical needs of the business.

ResponsibilitiesOwn and enhance BI infrastructure
  • Administer and optimize our Snowflake data warehouse (roles, performance, cost control, governance).

  • Maintain and scale dbt projects including core models, tests, documentation, semantic modeling, and deployments.

  • Manage GitLab pipelines/runners to support robust CI/CD for BI assets.

  • Oversee job scheduling and orchestration for BI transformations and data flows.

  • Own ingestion pipelines relevant to BI data needs.

Bridge the gap between Data Engineering and BI
  • Collaborate with Data Engineering to understand upstream mesh data products with BI analysts to understand business logic, metrics definitions, and performance targets.

  • Extend mesh data into curated BI data layers optimized for analytics.

  • Design data structures that support accurate, scalable analytics (fact tables, dimensions, semantic layers).

  • Participate in architectural decisions to align upstream pipelines with downstream analytical requirements.

Deliver data experiences to end users
  • Build custom solutions (APIs, extracts, materialized datasets, governed marts) to deliver data in the right format for each use case.

  • Implement robust testing, monitoring, and reliability processes for BI pipelines.

  • Ensure fast, reliable data availability for business stakeholders.

Support and guide BI initiatives
  • Partner with BI Analysts to maintain a reliable modeling environment and help unblock analytical workflows.

  • Recommend the most effective data modeling approaches and development processes, considering business priorities and resource limits.

  • Participate in tooling evaluations and decisions, ensuring solutions fit BI use cases and organizational architecture.

  • Provide clarity in ambiguous situations and advise leadership on risks, dependencies, and sequencing of work.

QualificationsRequired
  • 3-5+ years as an Analytics Engineer, Data Engineer, or similar role with a strong analytics orientation.

  • Strong proficiency with Snowflake and familiarity with AWS analytics services (Redshift, Athena, S3, SageMaker, etc.).

  • Expertise in SQL, Python, and Spark for data processing, automation, and custom integrations.

  • Experience with dbt and modern data modeling best practices.

  • Hands-on experience with Git-based CI/CD workflows (GitLab preferred).

  • Familiarity with ingestion tools such as Fivetran.

  • Proven ability to translate business requirements and metric definitions into robust, scalable data models.

  • Strong communication and stakeholder management skills.

Nice-to-Have
  • Experience supporting BI or analytics teams directly.

  • Knowledge of semantic layers, metrics stores, or analytics engineering frameworks.

  • Python experience for automation, orchestration, or custom integrations.

  • Familiarity with data mesh principles and domain-oriented data products.

  • Experience optimizing cross-cloud data architecture or hybrid environments.

Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.

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