> Markdown version of [/jobs/ext/4350675-senior-enterprise-technical-lead](https://www.wearedevelopers.com/jobs/ext/4350675-senior-enterprise-technical-lead). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Enterprise Technical Lead - **Company:** NM2TECH LIMITED LIABILITY COMPANY - **Location:** Washington, DC, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Big Data, Business Software, Code Review, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Warehousing, Python (Programming Language), Machine Learning, Cloud Services, Standard Sql, SAS (Software), Systems Integration, Tableau (Software), Data Processing, Scripting, Information Technology, Data Analytics - **Published:** October 15, 2026 - **Apply:** https://www.nettemps.com/us/en/WBE14DD8BB675DE24EF.ntap ## About the Role 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 ## Description 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.