Steampunk - McLean, VA
posted 4 months ago
In today's rapidly evolving technology landscape, an organization's data has never been a more important aspect in achieving mission and business goals. Our data exploitation experts work with our clients to support their mission and business goals by creating and executing a comprehensive data strategy using the best technology and techniques, given the challenge. At Steampunk, our goal is to build and execute a data strategy for our clients to coordinate data collection and generation, to align the organization and its data assets in support of the mission, and ultimately to realize mission goals with the strongest effectiveness possible. For our clients, data is a strategic asset. They are looking to become a facts-based, data-driven, customer-focused organization. To help realize this goal, they are leveraging visual analytics platforms to analyze, visualize, and share information. At Steampunk, you will design and develop solutions to high-impact, complex data problems, working with the best data practitioners around. Our data exploitation approach is tightly integrated with Human-Centered Design and DevSecOps. We are looking for a seasoned Data Solution Architect to work with our team and our clients to develop enterprise-grade data platforms, services, pipelines, data models, visualizations, and more! The Data Solution Architect needs to be a technologist with excellent communication and customer service skills and a passion for data and problem-solving. This role spans the spectrum of data capabilities, from data vision and strategy all the way through data science. The responsibilities include designing greenfield data solution stacks in the cloud or on-premises, using the latest data services, products, technology, and industry best practices. You will be architecting the migration of legacy data environments with performance and reliability. Data Architecture contributions include assessing and understanding data sources, data models and schemas, and data workflows. Data Engineering contributions include assessing, understanding, and designing ETL jobs, data pipelines, and workflows. BI and Data Visualization contributions include assessing, understanding, and designing reports, selecting BI tools, creating dynamic dashboards, and setting up data pipelines in support of dashboards and reports. Data Science contributions include assessing, understanding, and designing machine learning and AI applications, designing MLOps pipelines, and supporting data scientists. You will also address technical inquiries concerning customization, integration, enterprise architecture, and general feature/functionality of data products. Experience in crafting data lakehouse solutions in the cloud (preferably AWS, alternatively Azure, GCP) is essential, including relational databases, data warehouses, data lakes, and distributed data systems. A broad understanding of the data exploitation lifecycle and capabilities is a key requirement, along with support for an Agile software development lifecycle. You will contribute to the growth of our Data Exploitation Practice!