Company Description Ex Parte provides our customers with the data and insight to make smart and informed decisions on the most important legal issues facing their organizations. We are is looking for talented, enthusiastic senior data engineers who share our passion for big data, AI, and machine learning and are excited by seemingly-impossible challenges. As an early employee, you must be amazingly entrepreneurial and thrive in a fast-paced environment where the solutions aren’t predefined. Every year, corporations spend more than $250B on litigation in the United States alone. And yet, critical decisions such as whether to litigate or settle, or where to file suit or which attorney to hire, are all made the same way they were 100 years ago. We are applying artificial intelligence, machine learning, and natural language processing to provide our customers with the insight they need to make highly informed decisions and gain a winning advantage. Think of it like Moneyball, but for a market more than 20x the size of Major League Baseball. Job Description Responsibilities Take ownership of end to end data quality Understand and Contribute to the event model design Build and automate testing frameworks around data ingestion pipelines. Write complex SQL queries on tables with hundreds of millions of records and ensure data integrity is maintained throughout the ETL lifecycle. Design test cases and write python/SQL scripts to validate data integrity and identify gaps and opportunities in our pipelines. Track data issues and work with team leads from discovery to resolution. Collaborate with the analytic teams to conduct data quality investigations, improve automation and tools. Review current tools and enhance them to help with data integrity. Qualifications Minimum Qualifications 5+ years of work experience in QA, preferably in data or relevant space Demonstrable knowledge, experience, skill, and proficiency with the following: Scrum/Agile methodologies SDLC Python (at least reading) SQL Experience with different facets of QA tests such as functional progression & regression, integration, performance, load, UAT, and operational readiness testing Must be self-motivated, able to work independently, and thrive in a fast-paced, multi-tasking, high productivity environment while maintaining excellent working relationships with people in a wide variety of functional areas Excellent verbal and written communication skills Preferred Qualifications Applied experience with Databricks and/or Azure ML Strong coding abilities in one or more scripting languages like Python or SQL Understanding of compliance, security, and risk domains along with associated patterns and data elements Use of one of the following vendor reporting solutions: PowerBI or Tableau Understanding of product and services activation, use, and transaction models and data Understanding of statistical analysis and machine learning tools and practices Understanding of Cloud-centric data processing and visualization approaches including SQL and NoSQL databases with exposure to Azure SQL, Azure Cosmos DB, Data Factory, Synapse, Azure Data Lake, etc Familiarity with Agile software delivery including application lifecycle mgmt (Jira/Azure DevOps/VSTS, Git). Additional Information All your information will be kept confidential according to EEO guidelines.

Company Description RapidSoft established in 2003, with a mission of providing clients with experiened and talented resources in timely manner. We specialize in in Independent Verification and Validation, Test Automation and DevOps, Static Code Analysis. Our Staffing division handles, niche staffing needs for  companies of all sizes by providing technically prescreened resources thus reducing the hiring life cycle. Less  Clutter of Resumes More Hires for clients. Job Description Duties and Responsibilities: • Develop data solutions in collaboration with other team members and software engineering teams that meet and anticipate business goals and strategies • Work with senior data science engineers in analyzing and understanding all aspects of data, including source, design, insight, technology and modeling • Develop and manage scalable data processing platforms for both exploratory and real-time analytics • Oversee and develop algorithms for quick data acquisition, analysis and evolution of the data model to improve search and recommendation engines. • Document and demonstrate solutions • Design system specifications and provide standards and best practices • Support and mentor junior data engineers by providing advice and coaching • Make informed decisions quickly and taking ownership of services and applications at scale • Be a persistent, creative problem solver, constantly striving to improve and iterate on both processes and technical solutions • Remain cool and effective in a crisis • Understand business needs and know how to create the tools to manage them • Take initiative, own the problem and own the solution • Other duties as assigned  Supervisory Responsibilities: • None  Minimum Qualifications: • Bachelor's Degree in Data Engineering, Computer Science, Information Technology, or a related discipline (or equivalent experience) • 8+ years experience in data engineering development • 5+ years experience working in object oriented programming languages such as Python or Java • Experience working in an Agile environment

• Define and maintain a data engineering roadmap; align technical priorities with business objectives and the Northrop Grumman data strategy. • Build and lead a high-performing, collaborative team; mentoring engineers on design patterns, code quality, data architecture, and career development. • Champion clean, modular architecture and enforce engineering best practices. • Drive end-to-end delivery of data pipelines in Databricks, ensuring reliability, scalability, and performance while meeting roadmap milestones. • Lead the migration to our Databricks enterprise lakehouse. • Collaborate with leaders and teams across various functions, including business management, business development, facilities, human resources, supply chain, and manufacturing.

• Design, model, and name tables, views, columns, and keys. • Maintain the CDW Meta Data Repository. • Validate data and support the Customer Enablement Team for data quality. • Demonstrate expertise in data modeling, including schema design and optimization. • Collaborate with data modelers to design scalable, normalized database architectures. • Apply deep knowledge of modeling concepts to support VA enterprise systems. • Define and implement system-level verification procedures and customer acceptance test protocols to ensure high-quality deliverables. • Review and validate test plans and procedures, ensuring compliance with contractual and industry standards. • Conduct in-depth data analysis to identify architectural migration patterns and resolve dependencies.