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Sr Enterprise Technical Lead

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Sr Enterprise Technical Lead

NM2TECH LLC.

Sr Enterprise Technical Lead

Skills

Google Cloud PlatformSQL QueriesData EngineeringTableauPythonData ScienceData VisualizationData AnalysisMachine LearningAIAWSAzure

10 days ago

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Important information


Contract type:

Permanent

Location:

Washington, DC, USA

Work mode:

Remote

Published on:

14 October 2026

What they need


NM2TECH is seeking a Senior Enterprise Technical Lead who is a hands-on expert in data analytics, visualization, and AI-driven solutions. This role requires a strong technical leader who actively contributes to development while guiding a team of analysts and data scientists.

The ideal candidate will have deep experience in Tableau, SAS, Python, and Artificial Intelligence / Machine Learning, and will play a key role in designing and delivering enterprise-scale analytics solutions. This is a working lead role, requiring both technical execution and team leadership. The ideal candidate will have an active BI or NACLC Public Trust security clearance, be a confident leader experienced in performing day-to-day tasks, a critical thinker and self-starter who takes ownership of assignments

Previous consulting experience using an agile delivery methodology is a plus.

Requirements :

Security Clearance:      Must possess active BI or NACLC Public Trust security clearance

·      Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or related field.

·      8+ years of hands-on experience in analytics, data science, or business intelligence.

·      2–4 years of technical leadership experience in analytics or data science teams.

·      Strong hands-on expertise in:

o  Tableau – dashboard development and enterprise visualization

o  SAS – statistical analysis and large-scale data processing

o  Python – data analysis, automation, and machine learning

·      Experience building AI / Machine Learning models for real-world business applications.

·      Strong SQL and data warehousing knowledge.

·      Experience working with large enterprise datasets and complex analytics environments.

·      Experience in a matrix structure and communicating with technical and non-technical people. Ability to develop and deliver presentations that simplify complex solutions/insights for non-technical audience a must

·      Excellent innovation, interpersonal, and communication skills required.

Preferred Qualifications:

·      Experience with cloud data platforms (AWS, Azure, or GCP).

·      Familiarity with data engineering pipelines and ETL frameworks.

·      Experience in integrating AI solutions into enterprise analytics platforms.

·      Exposure to Agile development environments.

Key Skills:

·      Advanced Analytics & Data Science

·      AI / Machine Learning Development

·      Tableau Dashboard Engineering

·      Statistical Modeling (SAS)

·      Python Programming for Data Science

·      Enterprise Data Architecture

·      Technical Leadership & Mentoring

·      Data Visualization & Storytelling

Key Responsibilities: Lead the design, development, and deployment of enterprise analytics solutions to support strategic business decision-making.

·      Serve as a hands-on technical lead, actively developing dashboards, analytics models, and data solutions.

·      Build and maintain interactive dashboards and reporting solutions using Tableau to deliver actionable insights.

·      Perform advanced data analysis, statistical modeling, and data processing using SAS and Python.

·      Develop and implement AI and machine learning models for predictive analytics, forecasting, and business optimization.

·      Write and optimize Python scripts and analytics workflows for data transformation, automation, and model development.

·      Collaborate with business stakeholders, product teams, and data engineers to translate business requirements into scalable analytics solutions.

·      Conduct code reviews and provide technical mentorship to analysts and data scientists.

·      Ensure data quality, governance, and best practices in analytics development and reporting.

·      Design and optimize data models, queries, and datasets to support high-performance analytics and visualization.

·      Communicate complex analytical findings and recommendations to technical and non-technical stakeholders.

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