Data Engineer

ECS Tech Inc•Arlington, VA

17h•$120,000 - $140,000•Hybrid

About The Position

ECS is seeking a Cybersecurity Data Engineer to join our growing team supporting the Cybersecurity and Infrastructure Security Agency's (CISA) Technical Engineering and Support Services (TESS) program. TESS is CISA's integrated, capability-driven mission ecosystem designed to scale across mission and delivery spaces within the DHS/CISA/Cybersecurity Division. This role services Strategic Narratives and related missions. This role supports the digital transformation of a public-sector agency leading government-wide efforts to secure IT infrastructure. Strong candidates will take advantage of modern approaches to technology, business delivery, and the use of data. The Data Engineer is responsible for collaborating with other analytics-segment developers to construct applications that combine data from various external sources with data maintained within the supported applications. Must be able to build and maintain data models, engineer data architectures, and develop data integrations such as Extract Transform and Load (ETL) workflows. Must work closely with other architecture and engineering disciplines to establish best practices for analysis, modeling, designing, and building business information systems.

Requirements

Must be a US Citizen.
Must be able to obtain a Public Trust Clearance.
Bachelor's Degree in computer science, information systems management, mathematics, engineering, or other relevant discipline.
3+ years of IT experience including experience in development of large-scale, complex data architectures.
Demonstrated ability to rapidly learn new technologies and methods in response to changing environments and requirements.
Ability to use delivery methods to plan and execute data-integration and -architecture tasks for self and others without extensive supervision.
Demonstrated ability to analyze operational environments and recognize essential elements of information and information elements within them. Experience with decomposing mission flows into information-exchange requirements.
Ability to design, model, build, and maintain data for complex, extensible and highly visible on premise and cloud-based data platforms.
Experience working in Agile environment leveraging advanced design and engineering best practices.
Knowledge of Data Management and Data Architecture concepts.
Knowledge of Data Warehousing and Big Data.
Knowledge of Data Analytics and applicable knowledge of Data Science concepts and tools.
Knowledge of Data integration and Data Quality.
Experience with Databases (i.e., MySQL, Postgres, Oracle), ETL Tools (i.e., Informatica, python), Git, and operational modeling (Unified Modeling Framework, DoD Architecture Framework, business process modeling notation).

Responsibilities

Conducts data-integration and data-warehouse development tasks in an Agile project-management framework guided by a data-solution methodology such as CRISP-DM, Blitzstein & Pfister’s (Harvard) data-science process, OSEMN, and others. Applies architectural, system-of-systems thinking to align data-integration and -storage segments with others in order to optimize solutions at the system level.
Collaborates with other data-technology stakeholders within the agency. Contributes thought leadership in identifying long-term actions contributing to progress towards digital-transformation.
Develops conceptual data models of clients’ mission environments. Reviews policy and procedure documents, interviews clients in order to identify essential elements of mission information.
Characterizes information elements in terms of entity, attributes, and interrelationships.
Translates conceptual data models into normalized, referentially-integrated data schema. Incorporating context about objective use cases and user interfaces to organize the schema for both data-quality management user-interface considerations. Deploys data schema into open-source relational database management systems available from agencies’ approved produce lists.
Inspects and evaluates source systems. Documents data architecture at source systems’ interfaces. Performs exploratory data analysis and data-quality assessments of data extracts from source systems. Provide recommendations and estimates on suitability of data for intended use cases, estimated effort to correct data-quality issues (cleanse), and to transform into referentially-integrated, normalized data schema.
Provide recommendations on data-storage and -management strategies and architectures. Evaluate end-to-end data-processing needs and recommend storage and transformation technologies and approaches that best functional and non-functional requirements derived from mission needs.
Implement, maintain, and evolve data-transformation and -integration logic to transform extracts from source systems into records for insertion into normalized, referentially-integrated data schema. Use open-source tools available from agency’s approved-product list.
Developed denormalized views of contents of normalized, referentially-integrated database for visualization, user-interface purposes.