Responsibilities
The Data Engineer works on unusually complex technical problems, develops highly innovative solutions, and exercises considerable independence in determining the approaches necessary to achieve desired results. The Data Engineer shall support the Sponsor's mission by applying technical expertise to complex data challenges while collaborating with cross-functional teams.
Responsibilities include, but are not limited to, the following:
- Designing and implementing scalable data architectures to support real-time data processing and integration, with a focus on enabling the mission while minimizing cost and complexity.
- Collaborating with the Data Scientist to effectively deliver data streams of interest and prioritize certain data types for quick analysis.
- Developing data pipelines to support data integration.
- Developing and maintaining data quality checks.
- Engaging with high-priority stakeholders to provide data-driven solutions.
- Working with downstream data repositories to ensure needs are met and data flow is optimized.
- Meeting the needs of customers unfamiliar with the data or data engineering concepts, including targeters and engineers.
- Developing data filtering and processing algorithms.
- Establishing new data flows to integrate external data sources into Sponsor repositories using AWS methods and non-traditional options.
- Ensuring compliance with relevant data stewardship, documentation, and security requirements.
- Providing technical leadership and direction in implementing enterprise information/data management practices.
- Leading and participating in information/data management projects, including the Enterprise Information Architecture, information models and flows, data dictionaries, data standards, and data quality processes and standards.
- Developing and maintaining the logical Enterprise Information Architecture that enables seamless information interoperability among transaction systems, document management systems, and information delivery systems.
Qualifications
- Must possess and be able to maintain a TS/SCI clearance with polygraph.
- Bachelor's degree (or equivalent experience) in the fields of Computer Science, Information Systems, Engineering, Business, or a related scientific or technical discipline.
- BS 10-12, MS 8-10, PhD 5-7
- Knowledge of and experience with the Sponsor's environment.
- Experience with the following:
- Cloud-based data platforms like AWS, GCP, or Azure.
- System architecture and implementation of data solutions.
- Data engineering tools and techniques.
- Programming languages such as Python, Java, or C++.
- Building data pipelines and integrating multiple data sources.
- Working with challenging data sets and developing data filtering and processing algorithms.
- Developing information architectures aligned with information lifecycle management.
- Performing conceptual, logical, and physical data modeling using data modeling tools and database design techniques in complex, large-scale data environments.
- Transactional data modeling, dimensional modeling, and object-oriented modeling.
- Developing scalable entity designs using advanced data structures (e.g., tall tables).
- Developing data models that support time dependencies, historical tracking, simple and complex taxonomies, and multilingual data.
- Creating data dictionaries, defining metadata management approaches, and establishing governance processes.
- Developing and implementing IT architecture plans, Enterprise Information Architecture standards and guidelines, software development methodologies, and strategic plans.
- Developing data sharing standards and architecting scalable service-oriented solutions.
- Creating enterprise models incorporating master and reference data.
- Solid understanding of transaction and information systems, data warehouses, data marts, ODS, MDM methodologies and life cycles, as well as ETL and MDM technologies.
- Knowledge of application modeling languages/techniques (e.g., UML, OML, entity relationship modeling, DFDs), including the ability to create and read the associated diagrams.
Desired
- Familiarity with data visualization tools such as Tableau or Power BI.
- Experience with machine learning frameworks such as TensorFlow or PyTorch.
- Experience with data quality management and data validation techniques.
- Ability to work with sensitive data sources and develop data anonymization algorithms.
Equal Pay Act
This is the projected compensation range for this position. There are differentiating factors that can impact a final salary/hourly rate, including, but not limited to, Contract Wage Determination, relevant work experience, skills and competencies that align to the specified role, geographic location (For Remote Opportunities), education and certifications as well as Federal Government Contract Labor categories. In addition, Arcfield invests in its employees beyond just compensation. Arcfield 's benefits offerings include, dependent upon position, Health Insurance, Life Insurance, Paid Time Off, Holiday Pay, Short Term and Long-Term Disability, Retirement and Savings, Learning and Development opportunities, wellness programs as well as other optional benefit elections. Min: $125,133.53 Max: $217,582.94
