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Senior Shopify Data Analyst Jobs in Colorado (NOW HIRING)

As the Senior Data & Analytics Specialist, you will be responsible for, but not limited to, the following: * Enterprise Data Platform & Engineering: Design, develop, and maintain the firm ...

As the Senior Data & Analytics Specialist, you will be responsible for, but not limited to, the following: * Enterprise Data Platform & Engineering: Design, develop, and maintain the firm ...

Senior Data Manager

Denver, CO

$69.25 - $92.75/hr

Responsibilities & Qualifications RESPONSIBILITIES The Senior Data Manager is expected to be able ... Experience with visual analytic tools like Microsoft Pivot, Palantir, or Visual Analytics.

Senior Business Analyst

Englewood, CO · On-site

$91K - $118K/yr

... , Data Warehouse, and AI Office teams * Accelerated adoption of Intelligent Automation and AI ... Working knowledge of billing platforms such as CSG, Recurly, Amdocs, or Shopify. * Familiarity with ...

Data Governance Analyst Location: Greenwood Village, CO | 4 days onsite, 1 remote Contract Type ... SVP-level stakeholders. If you thrive when priorities shift quickly and want a role with real ...

As a healthcare analyst, you will be performing research/analysis based on the client data followed ... You will be reporting to the Senior Consultant. About our client: They are an equal opportunity ...

Showing results 41-60

Senior Shopify Data Analyst information

What does a senior Shopify data analyst do?

A Senior Shopify Data Analyst is responsible for collecting, analyzing, and interpreting data from Shopify stores to inform business decisions and optimize e-commerce performance. They use data analytics tools to track sales, customer behavior, product performance, and marketing effectiveness. Their insights help businesses improve conversion rates, increase revenue, and streamline operations. Additionally, they often create dashboards and reports for stakeholders and collaborate with marketing, sales, and product teams to develop data-driven strategies.

How does a senior Shopify data analyst typically collaborate with marketing and e-commerce teams to drive business growth?

A Senior Shopify Data Analyst regularly partners with marketing and e-commerce teams to analyze customer behavior, track campaign performance, and identify trends that can inform strategic decisions. They provide actionable insights by creating dashboards and reports, often translating complex data into clear recommendations for optimizing product listings, pricing strategies, and promotional efforts. Effective collaboration requires strong communication skills and an in-depth understanding of both Shopify analytics tools and the business's overall objectives. These analysts often attend cross-functional meetings to ensure data-driven decisions are integrated into daily operations.

What are the key skills and qualifications needed to thrive as a senior Shopify data analyst, and why are they important?

A Senior Shopify Data Analyst should possess strong analytical skills, deep knowledge of e-commerce data, and experience with data modeling, usually backed by a degree in analytics, statistics, or a related field. Expertise in using Shopify's analytics tools, SQL, BI software like Tableau or Looker, and familiarity with data integration platforms is essential. Excellent problem-solving, communication, and stakeholder management skills help translate complex data into actionable business insights. These abilities are crucial for driving data-informed decisions that optimize store performance and support business growth in a competitive e-commerce landscape.

What is the difference between Senior Shopify Data Analyst vs Shopify Data Analyst?

AspectSenior Shopify Data AnalystShopify Data Analyst
Required CredentialsBachelor's degree in Data Science, Analytics, or related field; experience with SQL, Excel, and Shopify analytics toolsBachelor's degree or equivalent; familiarity with Shopify platform and basic data analysis skills
Work EnvironmentMid to large e-commerce companies, often in a team setting, focusing on complex data projectsStartups or small to medium-sized e-commerce businesses, handling routine data tasks
Employer & Industry UsageUsed across e-commerce, retail, and digital marketing sectorsPrimarily in e-commerce and online retail sectors using Shopify platform

The main difference between a Senior Shopify Data Analyst and a Shopify Data Analyst lies in experience and scope. Senior analysts typically handle more complex data projects, require advanced skills, and often have leadership responsibilities. Shopify Data Analysts focus on routine data analysis and reporting within Shopify stores. Both roles are essential in e-commerce, but the senior position demands greater expertise and strategic input.

What are the most commonly searched types of Shopify Data Analyst jobs in Colorado?

The most popular types of Shopify Data Analyst jobs in Colorado are:

What cities in Colorado are hiring for Senior Shopify Data Analyst jobs?

Cities in Colorado with the most Senior Shopify Data Analyst job openings:

Senior Data & Analytics Specialist

Holthouse Carlin & Van Trigt LLP

Denver, CO • On-site

$123 - $150/hr

Other

Posted 6 days ago


Job description

Come for the Challenge. Stay for the Experience.

At HCVT, we believe every challenge presents an opportunity to positively impact our clients and people. Talented and ambitious individuals who seek limitless professional opportunities thrive at HCVT. Our team is known for its technical skill and ability to help clients address complex business issues all while investing in and supporting our people to provide a rewarding employee experience.

What We Do and Who We Serve

We offer Tax, Audit, Advisory, and Business Management services to our clients, which include private and public companies, high-net-worth individuals, and family offices. We also specialize in serving clients across the following industries: Private Equity, Real Estate & Hospitality, Media & Entertainment, High-Net-Worth Individuals, Manufacturing & Distribution, Professional Services Firms, Technology, Healthcare, Nonprofit Organizations, and Affordable Housing.

We Live Our Core Values

Our values guide us in our day-to-day interactions with our clients and each other—Integrity at our Core; Building Success Together; Passion for Excellence; and Diversity, Equity, & Inclusion. We are focused and committed to the needs of our clients and our team.

Discover How Far You Can Go.

Opportunities abound at HCVT. Our firm has experienced steady growth since its founding in 1991 and continues to expand its client service offerings, creating new opportunities for professionals to grow their careers. We make significant investments in training and provide interesting, diverse, and intellectually stimulating work for our teams—the kind of work that helps you develop and refine your skills to advance in the profession.

Hybrid Work

HCVT currently offers a hybrid work model that allows eligible employees to work both remotely and in the office, based on business needs and team coordination. When working remotely, employees are expected to meet the same performance standards, adhere to the same policies, and maintain the same level of communication, collaboration, and responsiveness as working in the office. Please note that this arrangement is not guaranteed and subject to change at any time. We will strive to provide reasonable notice of any changes to your work location or schedule whenever possible.

About the Role

The Senior Data & Analytics Specialist is responsible for designing, building, and advancing the firm's enterprise data and analytics capabilities. This role combines expertise in data engineering, business intelligence, advanced analytics, and machine learning to deliver scalable data platforms, actionable business insights, and AI-ready data assets. Working closely with business and technology leaders, the position transforms enterprise data into trusted information that improves decision‑making, operational efficiency, and client outcomes.

As the Senior Data & Analytics Specialist, you will be responsible for, but not limited to, the following:
  • Enterprise Data Platform & Engineering: Design, develop, and maintain the firm's enterprise data platform, including data warehouses, data lakes, semantic models, and data pipelines. Build scalable ETL/ELT processes that integrate information across Finance, Tax, Audit, Advisory, Operations, and other business systems while ensuring data quality, reliability, governance, and performance. Define data models, standards, and architecture that support reporting, analytics, machine learning, and AI initiatives.
  • Data Analytics & Business Intelligence: Develop modern analytics solutions that provide meaningful insights into business performance and operations. Design and deliver executive dashboards, KPIs, operational reporting, and self‑service analytics using Power BI and Microsoft Fabric. Partner with business stakeholders to translate analytical requirements into scalable reporting solutions while establishing best practices for data visualization, metric definitions, and analytics governance.
  • Advanced Analytics & Data Science: Apply statistical analysis, predictive modeling, forecasting, and machine learning techniques to solve complex business problems. Build analytical models that improve operational efficiency, identify trends, predict outcomes, and support strategic decision‑making. Evaluate model performance, improve accuracy, and operationalize analytical solutions for enterprise use.
  • AI-Ready Data & Intelligent Solutions: Develop governed, high‑quality data assets that enable AI applications, intelligent automation, and generative AI solutions. Support modern AI capabilities through semantic models, vector‑ready datasets, retrieval pipelines, and data preparation processes that improve the accuracy, reliability, and scalability of AI‑enabled business solutions. Partner with software engineering teams to integrate analytics and machine learning capabilities into enterprise applications and AI agents.
  • Technical Leadership & Data Strategy: Provide technical leadership in enterprise data architecture, analytics technologies, and modern data engineering practices. Evaluate emerging tools and technologies, recommend improvements to the firm's data ecosystem, and contribute to the long‑term analytics and AI strategy. Promote engineering best practices, data governance standards, automation, and continuous improvement across the analytics platform.
We expect that our Staff Azure Cloud Engineer will have the following qualifications:
  • 5+ years of progressive experience in data engineering, data analytics, data science, business intelligence, or related technical disciplines.
  • Degree in Computer Science, Data Science, Analytics, Engineering, or a related technical discipline.
  • Strong experience designing relational databases, dimensional models, data warehouses, and scalable data pipelines.
  • Advanced proficiency with SQL and Python, including data transformation, automation, and analytical development.
  • Experience designing and implementing ETL/ELT processes, data integration solutions, and enterprise data models.
  • Working knowledge of statistical analysis, predictive modeling, machine learning, and model evaluation techniques.
  • Knowledge of DevOps, CI/CD, Git, and Infrastructure-as-Code practices for analytics platforms.
  • Experience with data governance, data quality, metadata management, and enterprise analytics best practices.
  • Strong analytical thinking, technical problem‑solving, and the ability to translate business requirements into scalable data solutions.
  • Excellent communication skills with the ability to explain complex technical concepts to business stakeholders.
Preferred Qualifications
  • Experience within professional services, consulting, financial services, or public accounting.
  • Hands‑on expertise with Microsoft Fabric, Azure Data Platform, Power BI, or comparable cloud‑based analytics platforms.
  • Experience with AI‑enabled data architectures, RAG pipelines, semantic search, vector databases, or LLM‑powered applications.
  • Experience building production machine learning or advanced analytics solutions.
  • Master’s Degree in Computer Science, Data Science, Analytics, Engineering, or a related technical discipline.
You Matter - HCVT provides a variety of benefits and perks that help sustain a healthy and thriving work environment.
  • Visit the Benefitssectionto learn more.

This salary range is specific to the state(s) listed and takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill set and education; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the range for this position is $123,000 to $150,000.

Connect with us:

LinkedIn,Instagram,Facebook,HCVT Website

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