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Sr Enterprise Technical Lead

Job in Washington, District of Columbia, 20022, USA
Listing for: NM2TECH LLC.
Full Time position
Listed on 2026-10-17
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineering, Data Scientist, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 170000 - 210000 USD Yearly USD 170000.00 210000.00 YEAR
Job Description & How to Apply Below
Position: Sr  Enterprise Technical Lead

NM2

TECH 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:
  • oTableau – dashboard development and enterprise visualization
  • oSAS – statistical analysis and large‑scale data processing
  • oPython – 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.
    Key

    Skills:
    • · Advanced Analytics & Data Science
    • · AI / Machine Learning Development
    • · 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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