The Analytics Enablement Manager will lead analytics engineers and drive a cohesive analytics strategy to enhance analytical quality and consistency across the organization. Responsibilities : • ...
The Analytics Enablement Manager will lead analytics engineers and drive a cohesive analytics strategy to enhance analytical quality and consistency across the organization. Responsibilities : • ...
The Analytics Enablement Manager is responsible for leading analytics engineers within Data Services while shaping and driving a cohesive, enterprisewide analytics strategy. This leader brings a ...
The Analytics Enablement Manager is responsible for leading analytics engineers within Data Services while shaping and driving a cohesive, enterprisewide analytics strategy. This leader brings a ...
The Analytics Enablement Manager is responsible for leading analytics engineers within Data Services while shaping and driving a cohesive, enterprise-wide analytics strategy. This leader brings a ...
The Analytics Enablement Manager is responsible for leading analytics engineers within Data Services while shaping and driving a cohesive, enterprise-wide analytics strategy. This leader brings a ...
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Quick apply
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Quick apply
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Analytic Engineer information
See Colorado salary details
$41K - $50.4K
3% of jobs
$50.4K - $59.8K
3% of jobs
$59.8K - $69.3K
4% of jobs
$69.3K - $78.7K
7% of jobs
$78.7K - $88.1K
6% of jobs
$88.9K is the 25th percentile. Wages below this are outliers.
$88.1K - $97.5K
6% of jobs
The median wage is $106K / yr.
$97.5K - $106.9K
21% of jobs
$106.9K - $116.3K
4% of jobs
$122.4K is the 75th percentile. Wages above this are outliers.
$116.3K - $125.8K
29% of jobs
$125.8K - $135.2K
2% of jobs
$135.2K - $144.6K
13% of jobs
$41K
$107K
$144.6K
How much do analytic engineer jobs pay per year?
What is the best synonym for analytic?
What is the difference between Analytic Engineer vs Data Engineer?
| Aspect | Analytic Engineer | Data Engineer |
|---|---|---|
| Credentials | Typically requires a degree in data science, statistics, or related fields; often certifications in SQL, Python, or cloud platforms | Requires a degree in computer science, software engineering, or related fields; certifications in cloud services, SQL, and data pipeline tools |
| Work Environment | Focuses on analyzing data, building data models, and creating dashboards; collaborates with data scientists and business teams | Builds and maintains data pipelines, databases, and infrastructure; works closely with data engineers and software developers |
| Industry Usage | Commonly found in analytics teams, business intelligence, and data-driven decision-making roles | Primarily in data infrastructure, big data projects, and data platform development |
In summary, Analytic Engineers focus on transforming data into insights through analysis and modeling, while Data Engineers build the infrastructure to support data collection and storage. Both roles are essential in data teams but serve different functions within the data ecosystem.
What do you mean by analytic?
What does it mean if someone is analytic?
Is analytic a good ability in Pokémon?

Sonepar USA rating
7.4
Based on 31 frontline employees who took The Breakroom Quiz
158th of 338 rated retail wholesalers
Job description
Sonepar USA is a company that supports its brands through a shared services model, fostering an inclusive culture. The Analytics Enablement Manager will lead analytics engineers and drive a cohesive analytics strategy to enhance analytical quality and consistency across the organization.
Responsibilities:
• Define and drive an enterprise analytics enablement strategy that improves analytical quality, consistency, and trust across Operating Companies and Sonepar Management Group.
• Establish clear expectations and best practices for analytical problem framing, metric definition, and solution design - independent of specific tools or platforms.
• Act as a strategic advisor to business and analytics leaders on when and how different analytics approaches and productivity tools should be used, based on business need and maturity.
• Partner closely with Data Governance to ensure analytics practices align to a unified governance model, including standards for metrics, documentation, reuse, and ownership.
• Manage and develop analytics engineers within the centralized Data Services team, setting direction for how analytical solutions are designed, reviewed, and enabled across the organization.
• Promote modern analytics engineering practices, including modular design, reuse, documentation, and performance‑aware modeling.
• Ensure analytics engineers are focused on enablement and leverage, not long‑term ownership of bespoke reporting.
• With the Data Product Manager, support alignment between central Data Services and distributed Operating Company / Sonepar Management Group analysts, reducing fragmentation and duplicated effort.
• Support analyst communities by identifying common analytical patterns, shared needs, and opportunities for standardization or reuse.
• Influence without direct authority - driving alignment through clarity, shared frameworks, and strong analytical reasoning.
• Help shift the organization from reactive, ad‑hoc reporting toward prioritized, outcome‑driven analytics work.
• Provide strategic guidance on analytical usage of Power BI and the broader Microsoft analytics ecosystem.
• Bring informed perspective on modern analytics stacks from prior experience (e.g., SQL‑based modeling, semantic layers, cloud data platforms), without requiring deep specialization in any single tool.
• Understand and advise on analytical use cases related to Sonepar’s in‑house productivity applications, while not directly managing or delivering those solutions.
Qualifications:
Required:
• Strong analytical problem‑solving orientation, with the ability to translate ambiguous business questions into clear, structured analytical approaches and articulate tradeoffs and assumptions.
• 7+ years of experience in analytics, analytics engineering, business intelligence, or a closely related field, including experience operating in complex, matrixed organizations.
• Demonstrated experience leading or influencing analytics engineers, analysts, or analytics communities through standards, coaching, and enablement.
• Proven exposure to modern analytics platforms and practices across multiple environments (e.g., cloud data platforms, semantic modeling, analytics engineering, BI tools), with the ability to apply best practices pragmatically.
• Strong understanding of analytics governance concepts, including metric consistency, reuse, documentation, data product ownership, and lifecycle management.
• Ability to operate effectively across centralized and federated analytics models, balancing autonomy with enterprise consistency.
• Excellent communication skills, with the ability to engage credibly with technical teams, business leaders, and senior executives.
• Comfort influencing without authority and navigating organizational ambiguity while maintaining focus on outcomes.
• Understanding of modern analytics architecture concepts, including data transformation patterns, semantic/metrics layers, and analytical model design.
• Familiarity with analytics development best practices such as version control, peer review, and environment promotion, sufficient to guide standards and reviews.
Preferred:
• Experience working across multiple companies or industries, with exposure to varying levels of analytics maturity.
• Background in analytics engineering, data analytics, or business intelligence with strong grounding in technical best practices (not just report development).
• Experience supporting or enabling distributed analyst communities.
• Familiarity with Power BI and the Microsoft Fabric ecosystem, paired with openness and credibility across other modern analytics tools and approaches.
• Experience working with relational databases and analytical data stores, including writing and reviewing SQL and understanding performance considerations.
• Working knowledge of Python for analytics, automation, and data transformation use cases.
• Foundational understanding of data engineering concepts, including data movement, transformations, and dependency management (hands‑on expertise not required).
Company:
Sonepar USA is a wholesale company providing electrical, industrial, and safety products. Founded in 1998, the company is headquartered in Charleston, USA, with a team of 10001+ employees. The company is currently Late Stage.
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