> Markdown version of [/jobs/ext/3876989-senior-technical-lead-data-analytics](https://www.wearedevelopers.com/jobs/ext/3876989-senior-technical-lead-data-analytics). 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 Technical Lead, Data Analytics - **Company:** Onyx Government Services - **Location:** Chantilly, VA, United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - $155,000.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Microsoft Azure, Big Data, Business Software, Code Review, 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 22, 2026 - **Apply:** https://www.careerjet.com/jobad/us4e47d350d41cbd0bdb9b484bece8da77 ## 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. Security Clearance: Must possess active BI or NACLC Public Trust security clearance. Location: Work is primarily remote with some onsite work in Washington, DC as required., Security Clearance: Must CURRENTLY possess active BI or NACLC Public Trust 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: * Tableau - dashboard development and enterprise visualization * SAS - statistical analysis and large-scale data processing * 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. ## 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. * Communicate complex analytical findings and recommendations to technical and non-technical stakeholders.