Join GDIT and be a part of the team of men and women that solve some of the world’s most complex technical challenges. The NCIS program is searching for a Senior Level Data Engineer to join their team in Quantico, VA.
The Naval Criminal Investigative Service (NCIS) is an organization of over 2,000 personnel of which 700 serve at HQ and the remaining staff serve at offices worldwide. NCIS is the Department of Navy (DON) component with primary responsibility for criminal investigation, law enforcement (LE), counter-terrorism (CT), counterintelligence (CI), and cyber matters. NCIS not only has primary responsibility for all criminal investigative, CI, CT, and cyber matters within the DON, but it also has exclusive investigative jurisdiction in non-combat matters involving actual, potential, or suspected criminal, terrorism, sabotage, espionage, and subversive activities.
NCIS provides the DON with threat status and warnings associated with terrorist, criminal, cyber, and counterintelligence activity throughout the world. NCIS is the only DON organization that has the information and responsibility to fuse and analyze the national intelligence and law enforcement information necessary to provide these warnings.
This position will support the NCIS Office of the Command Data Officer (OCDO) and will be responsible for advancing the agency’s mission of investigating and defeating criminal, terrorist, and foreign intelligence threats to the DON – in the maritime domain, ashore, and in cyberspace. The NCIS OCDO is committed to supporting the NCIS mission through the implementation of a modern, integrated internal data infrastructure with a focus primarily on exploiting the established data foundation to make internal and customer-centric business processes as effective and efficient as possible, laying the foundation for cognitive capabilities that can sense and respond to both internal and external customer data needs. The OCDO will also focus on expanding the organization’s data ecosystem to include context-rich data while maintaining the agility needed to spark innovation.
As and intregal part of the OCDO, you will perform the following functions:
Establish shared operational data and integrated enterprise data, all while managing and/or improving data quality and security through the creation of business-driven governance structures and culture change management.
Establish data policies, standards, and procedures that improve data quality, availability, accessibility, security, usability, and enforcement of enterprise information management (EIM) program requirements.
Establish enterprise standards – including a uniform and repeatable system development lifecycle methodology for Reference Data and Master Data (e.g., a common set of standards for data naming, abbreviations, and acronyms).
Develop a data catalog to help NCIS organize and find data stored in their many systems. The data catalog shall include information about tables, files, and databases from the NCIS Enterprise Resource Planning (ERP), human resources (HR), finance, capability platforms, and social media feeds. The data catalog must also show where all the data entities are located.
Develop a Master Data Management (MDM) Plan that focuses on the technology, tools, and processes ensuring master data is coordinated across the NCIS enterprise. MDM is a method used to define and manage the critical data of an organization to provide, with data integration, a single point of reference. The data that is mastered may include reference data – the set of permissible values, and the analytical data supporting decision making. MDM provides a unified master data service intended to provide accurate, consistent and complete master data across the NCIS enterprise and to business partners.
Recommend solutions based on performing industry-specific analysis, such as case studies describing data management best practices, identifying trends across the industry.
Optimize and consolidate business and operational data while augmenting it with data about, and often generated by customers. Expand the data infrastructure to include sensor, device data, and other data sources.
Make recommendations to improve the efficiency and effectiveness in how NCIS acquires, stores, manages, shares and applies its data.
Engage business users and stakeholders for the increased release of actionable high-quality data on key operational and tactical activities at NCIS.
Develop technology solutions to provide the platform, training, and standardized tools enabling querying, data mining, statistical analysis, reporting, scenario modeling, data visualization, and dash-boarding, and processes for a centralized, or analytics as a service model, allowing for the sharing of data across the enterprise from a common hub, facilitates cross-organizational data initiatives due to its enterprise-wide view of data assets and needs.
Identify and manage risks proactively.
Required: Bachelor's or master's degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field [or equivalent work experience].
Preferred: Advanced degree in computer science (MS), statistics, applied mathematics (Ph.D.), information science (MIS), data management, information systems, information science (post-graduation diploma or related) or a related quantitative field [or equivalent work experience].
Required: Minimum six years or more of work experience in data management disciplines including [data integration, modeling, optimization and data quality], and/or other areas directly relevant to data engineering responsibilities and tasks.
Strong experience with advanced analytics tools for Object-oriented/object function scripting using languages such as R, Python, Java, and C++.
Strong ability to design, build and manage data pipelines for data structures encompassing:
The ability to work with both IT and business in integrating analytics and data science output into business processes and workflows.
Strong experience with popular database programming languages including SQL and PL/SQL for relational databases
Preferred: Certifications on upcoming NoSQL/Hadoop oriented databases like MongoDB, Cassandra are preferred but not required for non-relational databases.
Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. Including:
Message-oriented data movement
API design and access]
Upcoming data ingestion and integration technologies such as [stream data integration, CEP and data virtualization.
Strong experience in working with SQL on Hadoop tools and experience working with technologies including HIVE, Impala, and Presto from an open source perspective and Hortonworks Data Flow (HDF), Dremio, Informatica, and Talend from a commercial vendor perspective.
Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production.
Strong experience in working with both open-source and commercial message queuing technologies such as Kafka, JMS, Azure Service Bus, Amazon Simple queuing Service, others], stream data integration technologies such as Apache Nifi, Apache Beam, Apache Kafka Streams, and Amazon Kinesis, and stream analytics technologies such as Apache Kafka KSQL Apache Spark Streaming Apache and Samza.
Basic experience working with popular data discovery, analytics and BI software tools to include Tableau, Qlik, and PowerBI (PowerBI is preferred) for semantic-layer-based data discovery.
Strong experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms.
Preferred: Basic understanding of popular open-source and commercial data science platforms such as Python, R, KNIME, and Alteryx is a strong plus but not required/compulsory.
Demonstrated success in working with large, heterogeneous datasets to extract business value using popular data preparation tools such as Trifacta, Paxata, and Unifi to reduce or even automate parts of the tedious data preparation tasks.
Basic experience in working with data governance, data quality, and data security teams, data stewards, and privacy and security officers in moving data pipelines into production with appropriate data quality, governance and security standards and certification.
Demonstrated ability to work across multiple deployment environments including cloud, on-premises and hybrid environments, multiple operating systems and through containerization techniques such as Docker, Kubernetes, and AWS Elastic Container Service.
Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data managers and consumers across an organization
Deep law enforcement (LE) information domain knowledge or previous experience working in LE would be a plus.
Required: Certifications as per Cybersecurity Workforce Management and Qualification Manual, SECNAV M-5239.2.
Required: candidates can be SCI-eligible, but must have their SSBI at a minimum of SECRET.
We are GDIT. The people supporting some of the most complex government, defense, and intelligence projects across the country. We deliver. Bringing the expertise needed to understand and advance critical missions. We transform. Shifting the ways clients invest in, integrate, and innovate technology solutions. We ensure today is safe and tomorrow is smarter. We are there. On the ground, beside our clients, in the lab, and everywhere in between. Offering the technology transformations, strategy, and mission services needed to get the job done.
GDIT is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status, or any other protected class.