NCIS Data Engineer | Active Secret clearance
About The Position
Transform technology into opportunity as a Data Engineer at GDIT. Shape what’s next for mission-critical government projects while shaping what’s next for your engineering career. The Naval Criminal Investigative Service (NCIS) is an organization of approximately 2,000 personnel of which 700 serve at HQ and the remaining staff serve at offices worldwide. NCIS is the DON component with primary responsibility for criminal investigation, law enforcement (LE), counterterrorism (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. MEANINGFUL WORK AND PERSONAL IMPACT As a Data Engineer, the work you’ll do at GDIT will be impactful to the mission of the IT Technology Operations division within the NCIS ITD organization in Quantico, VA: This position 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. It will design and build a data hub that collects, stores, aggregates, and process raw data, to include law enforcement data into clean, usable formats for analysis, data visualization, and Machine Learning. It will promote and improve the quality of the data as they build out the architecture and data models while providing innovative ways to implement mission requirements and sustain clean, accurate data that is accessible both automated to systems/applications, DON Jupiter platform and implement security as designated to data by governance. It will focus on expanding the organization’s data ecosystem to include context-rich data while maintaining the agility needed to spark innovation.
Requirements
- Active Secret clearance. Must be able to successfully obtain a TS/SCI post hire.
- Minimum 10 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 Python, Java, and Scala.
- Strong ability to design, build and manage data pipelines for data structures encompassing: Data Transformation, Data Models, Schemas, Metadata, Workload Management.
- 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.
- 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: ETL/ELT, Data Replication/CDC, Message-oriented data movement, API design and access, Upcoming data integration technologies such as [stream data integration, CEP and data virtualization.
- Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helps to move them in production.
- Demonstrated success in working with large, heterogeneous datasets to extract business value using popular data preparation tools such as Databricks, 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.
- Bachelor's Degree in a technical discipline discipline; an additional 4 years of experience may be considered in lieu of degree.
- US Citizenship Required.
Nice To Haves
- Knowledge and experience with Machine Learning, AI and data analytics a plus.
- Experience working in a Data Management/CDO office a plus.
- Deep law enforcement (LE) information domain knowledge or previous experience working in LE, DoW and/or DON a plus.
- CompTIA Security+ CE required; AWS Certified Data Engineer – Associate Data Engineer Associate Cert desired.
- Experience with Databricks, Snowflake, Apache Kafka, Airflow, Spark, ETL Tools
- Experience with DON Jupiter
Responsibilities
- Design and build a data hub that collects, stores, aggregates, and process raw data, to include law enforcement data into clean, usable formats for analysis, data visualization, and Machine Learning.
- Promote and improve the quality of the data as they build out the architecture and data models while providing innovative ways to implement mission requirements and sustain clean, accurate data that is accessible both automated to systems/applications, DON Jupiter platform and implement security as designated to data by governance.
- Focus on expanding the organization’s data ecosystem to include context-rich data while maintaining the agility needed to spark innovation.
- Design, build, and manage scalable end-to-end data pipelines for data structures, encompassing data transformation, data models, data schemas, metadata and workload management.
- Provide IT expertise for decision makers to build out a new data environment (data hub) and transition the agency to data driven processes.
- Identify data generators/sources, develop a data acquisition and integration strategy, develop and implement best practice for data governance, data quality, data storage, and data usage in analytics and business intelligence.
- Build and have in-depth knowledge in data hubs and various forms of data housing, warehousing, lakes and marts.
- Manage data processes facilitating the handling of data via IT infrastructure - data hub, application, cloud and network resources.
- Apply knowledge and experience of cloud architectures/platforms and integration of data from on-premises to the cloud.
- Perform data cleansing and management to include improvement to meet operational needs.
- 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).
- Recommend in the development of improvement/updates to the data environment, implementing schema changes and advise on application and data source updates to keep data accurate and compliant with data governance model.
- 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.
- Provide documentation of data engineering activities such as SOPs.
- Establish data policies, standards, and procedures that improve data quality, availability, accessibility, security, usability, and enforcement of enterprise information management (EIM) program requirements.
Benefits
- Comprehensive benefits and wellness packages
- 401K with company match
- Competitive pay
- Paid time off
- Variety of medical plan options, some with Health Savings Accounts
- Dental plan options
- Vision plan
- 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match.
- Full flex work weeks where possible
- Variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave.
- Short and long-term disability benefits
- Life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
