Senior Data & AI Visualization Engineer

Ready to turn raw data into stories that empower decision-makers? In this role, you’ll own the data pipeline from aggregation to visual representation, building clear dashboards using Python and Jupyter. You’ll keep customer dataflows pristine and help us push boundaries with cutting-edge AI and NLP tools.

Act as a key translator between raw, complex mission data and actionable strategic insight. You won't just process numbers—you’ll craft compelling data visual stories, build dynamic dashboards, and untangle complex customer dataflows. If you thrive on taking massive, messy datasets, curating them to perfection, and transforming them into clear visual insights using Python and modern data science toolkits, you’ll fit right in with our client's team.

Required Skills

Programming & Environment: Deep technical proficiency with Python and extensive experience using Jupyter Notebooks for data manipulation, analysis, and prototyping.

Data Visualization & Dashboards: Demonstrated ability to present complex data findings clearly using visualization tools, custom charting libraries, and interactive dashboard platforms.

Dataflow & Processing: Hands-on experience working directly with customer dataflows, data pipeline architectures, continuous processing, and large-scale data aggregation.

Data Curation & Quality Assurance: Proven track record of evaluating large datasets to spot anomalies, correct structural/logic errors, and curate high-integrity data outputs.

AI & Machine Learning: Experience exploring, fine-tuning, or integrating AI models and Large Language Models (LLMs) into data workflows.

Natural Language Processing (NLP): Familiarity with NLP techniques, frameworks, and libraries (e.g., spaCy, NLTK, Hugging Face) for text analytics and unstructured data extraction.

Big Data Frameworks: Experience with distributed computing systems (e.g., PySpark, Hadoop, ElasticSearch) for managing large-scale enterprise data.

Collaborative Engineering: Familiarity with Agile development practices, CI/CD pipelines, and version control tools (Git).