We are looking for seasoned Data Technical Lead to work with our team and our clients to develop enterprise grade data platforms, services, pipelines, data models, visualizations, and more! The Tech Lead needs to be a technologist with excellent communication and customer service skills and a passion for data and problem solving.

MEANINGFUL WORK AND PERSONAL IMPACT

This role involves technical and thought leadership across the spectrum of data capabilities, from data vision and strategy all the way through data science.

Designing and leading the implementation of greenfield data solution stacks in the cloud or on premises, using the latest data services, products, technology, and industry best practicesExpand upon existing models to estimate how long it will take clients to process digital forms/applications and to present relevant information to users about their application processing journeyDevelop and deploy personalized Application Processing Time predictive models for additional services/forms as prioritized by clientAdd integration points for intelligent automated help agent to connect with external applications and/or data sources, to increase the agent’s effectiveness and accuracyCreate and implement data cleaning and processing strategies to ensure unstructured data is appropriate to present to the end user/customerAnalyze customer data and biometrics to identify key data points for confirming a customer’s identityDesign and implement data acquisition pipelines to ensure clean structured, and high-quality data ingestion from a web application with form-based inputs, applying validation, transformation, and deduplication techniques to enhance data integrityDevelop scalable data integration solutions by enabling real-time data sharing across enterprise systems using technologies (e.g., Kafka, AWS Kinesis, oar Apache Pulsar), ensuring seamless interoperability and adherence to data governance standardsData Architecture contributions include assessing, understanding, and implementing data sources, data models and schemas, and data workflowsData Engineering contributions include assessing, understanding, designing, and implementing ETL jobs, data pipelines, and workflows Analyze, validate, and create an ETL process to transition from a transaction-based model to a customer-centric modelData Science contributions include assessing, understanding, designing, and implementing machine learning and AI applications, designing MLOps pipelines, and supporting data scientistsAddressing technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of data productsEnhance chatbot intelligence and user experience by refining LLM and natural language processing (NLP) models, improving response accuracy, and optimizing conversational flows using machine learning techniques and user interaction data Support refactoring and optimizing chatbot architecture to improve scalability, efficiency, and maintainability , leveraging advanced AI/ML techniques, integrating with modern data pipelines, and implementing robust monitoring and analytics for continuous improvementKey must have skill sets – broad understanding of data exploitation lifecycle and capabilities, technical leadership in the data fieldSupport an Agile software development lifecycle

WHAT YOU’LL NEED TO SUCCEED

Education: Bachelor degree preferred and 5+ years of related experienceAbility to obtain a DHS Public Trust clearance (USCIS)US Citizenship required5+ years industry experience leading the design and implementation of data systems10+ years direct experience in Data Solutions with experience in tools such as:Big data tools: SparkRelational databases: Amazon RDS (PostgreSQL)Cloud Services: AWS services including RDS, ECS, EKS, ElastiCache, SESData pipeline and workflow management tools: Jenkins (for automation and CI/CD in data workflows)Data science tools/language: Python (data preparation and analysis libraries)Object oriented/scripting languages: PythonVersion control and collaboration: GitHubAdvanced working SQL knowledge and experience working with relational databases, query authoring and optimization (SQL) as well as working familiarity with a variety of databases.Experience with MLOps frameworks and exposure/understanding of DevOpsExperience with containerized environments such as ECS and EKS for data applicationsExperience with message queuing, stream processing, such as Amazon SQS and highly scalable ‘big data’ data stores.Experience processing, analyzing, extracting, and manipulating structured and unstructured data for analysisExperience architecting data systems, including transaction and analytical (data warehouse) architecturesExperience working in an Agile environmentExperience supporting project teams of developers and data scientists who build web-based interfaces, dashboards, reports, and analytics/machine learning models
GDIT IS YOUR PLACE
At GDIT, the mission is our purpose, and our people are at the center of everything we do.
● Growth: AI-powered career tool that identifies career steps and learning opportunities
● Support: An internal mobility team focused on helping you achieve your career goals
● Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
● Flexibility: Full-flex work week to own your priorities at work and at home
● Community: Award-winning culture of innovation and a military-friendly workplace

OWN YOUR OPPORTUNITY
Explore an enterprise IT career at GDIT and you’ll find endless opportunities to grow alongside colleagues who share your desire to drive operations forward.