採用
Required Skills
Power BI
Tableau
Databricks
Python
SQL
Data modeling
DAX
Communication
Teaching
Position Summary:
The AI/BI Enablement Specialist plays a critical role in empowering business and technical teams to leverage modern analytics, AI-assisted workflows, and data visualization tools. This role combines technical expertise in leading analytics & AI Agentic platforms— BI Tools (e.g. Power BI, Tableau), Data platforms (e.g. Databricks), Low Code enablers (e.g. Dataiku), Agentic AI tools (e.g. Copilot Studio), Workflow Orchestrators (e.g. n8n) —with strong communication, training, and solution design skills to drive enterprise-wide data literacy and self service analytics adoption.
The ideal candidate is a blend of educator, solution architect, and platform strategist, capable of enabling end users while ensuring alignment with governance, best practices, and enterprise data standards.
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Key Responsibilities
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Serve as a subject matter expert (SME) for Power BI, Tableau, Databricks, Dataiku, Copilot Studio, n8n AI/BI capabilities, guiding users on optimal feature usage, patterns, and solution approaches.
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Develop and deliver enablement assets such as training sessions, office hours, documentation, demos, and hands-on workshops.
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Promote self-service analytics and AI by advising users on how to build performant, scalable dashboards, workflows, machine learning pipelines and GenAI solutions.
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Partner with business to understand analytical and AI needs and translate them into scalable solutions.
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Provide guidance on prompt engineering, responsible AI usage, and integration of AI/ML models into analytical workflows.
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Assist users in designing and optimizing Power BI and Tableau dashboards, including data modeling, DAX/LOD expressions, performance tuning, and visualization best practices.
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Provide guidance on Databricks workflows including Delta Lake, notebooks, Spark optimization, and AI/ML use cases.
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Troubleshoot platform-related issues, helping teams resolve technical blockers.
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Ensure adherence to proper data management and governance practices.
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Partner with data engineering and platform teams to align on architecture, integrations, and usage patterns.
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Foster a strong internal analytics community through forums, user groups, knowledge-sharing events, and newsletters.
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Collect user feedback to identify pain points, prioritize enhancements, and evolve training programs.
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Demonstrate and evangelize productivity enhancements across analytics, data science and AI.
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Required Qualifications
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3–7 years of experience in analytics, BI development, data science, or data engineering.
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Advanced proficiency in Power BI (data modeling, DAX, Power Query) and Tableau (LOD, dashboard optimization).
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Hands-on experience with Databricks (Spark, Delta Lake, SQL, Python notebooks).
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Practical experience with Copilot Studio, n8n, … (visual flows, AI/ML pipelines, automation/agents, deployment).
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Strong understanding of data warehousing concepts, semantic modeling, and ETL/ELT design.
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Excellent communication, teaching, and documentation skills.
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Proven ability to translate business requirements into technical solutions.
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Preferred Qualifications
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Experience implementing or managing enterprise BI platforms.
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Knowledge of Azure and AWS cloud ecosystems.
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Familiarity with MLOps, CI/CD, and governance frameworks.
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Experience hosting workshops, communities of practice, or internal training programs.
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Certifications in Power BI, Tableau, Databricks, or Dataiku are a plus.
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Competencies
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Customer-Centric Mindset – Passion for enabling others and simplifying complexity.
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Technical Curiosity – Strong desire to explore new tools, features, and AI/analytics trends.
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Collaboration & Influence – Ability to work cross-functionally with business, IT, and data teams.
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Structured Communication – Can explain complex concepts in simple, practical terms.
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Problem Solving – Strong analytical thinking with a bias toward action and continuous improvement.
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About NXP Semiconductors
Reviews
3.9
44 reviews
Work Life Balance
3.8
Compensation
3.9
Culture
4.1
Career
3.6
Management
3.8
73%
Recommend to a Friend
Pros
Competitive compensation and benefits
Good work-life balance and flexible environment
Interesting projects and challenges
Cons
Room for improvement in processes
Work-life balance varies by team
Internal communication could improve
Salary Ranges
267 data points
Junior/L3
L3
Junior/L3 · Data Scientist
0 reports
$114,000
total / year
Base
$99,000
Stock
-
Bonus
$15,000
$96,900
$131,100
Interview Experience
42 interviews
Difficulty
3.1
/ 5
Duration
14-28 weeks
Offer Rate
33%
Experience
Positive 69%
Neutral 13%
Negative 18%
Interview Process
1
Phone Screen
2
Technical Interview
3
Hiring Manager
4
Team Fit
Common Questions
Technical skills
Past experience
Team collaboration
Problem solving
News & Buzz
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