ICF is seeking a highly capable
HR Data Engineer / Data Scientist to support a large federal client in modernizing its enterprise learning and workforce data ecosystem. This role centers on designing and sustaining a scalable data integration capability that unifies multiple workforce-related data sources into a consistent, validated structure suitable for downstream HR and training systems. This position requires expertise in enterprise data engineering, workflow automation, data quality frameworks, metadata governance, and the translation of complex business rules into reliable technical logic. The ideal candidate brings experience working with HR, identity, or workforce-related datasets in large organizations and can partner directly with senior stakeholders across technical and business domains.
Prior experience working in federally-regulated environments and proximity to the DC-Maryland-Virginia (DMV) area with the ability to go onsite as needed is strongly preferred.
Key Responsibilities - Design, build, and maintain automated pipelines that unify multiple HR and workforce-related datasets into standardized, validated outputs.
- Develop and document transformation rules, business logic, mapping structures, and data quality checks to ensure accuracy and consistency.
- Create scalable workflows for ingesting structured and semi-structured data from diverse systems with varying formats and update cycles.
- Implement validation routines, anomaly detection, and error-handling mechanisms to maintain reliable, high-quality data products.
- Produce well-structured, standardized outputs compatible with enterprise learning or workforce management platforms.
- Collaborate with technical and non-technical stakeholders to refine requirements, resolve data ambiguities, and support decision-making.
- Maintain alignment with enterprise-wide data standards, schemas, and governance guidance as they evolve.
- Participate in cross-team or cross-agency coordination forums to represent program needs and communicate the impact of data-related decisions.
- Develop and execute test plans, including business-rule validation, regression checks, and iterative QA cycles.
- Identify process improvements, integration gaps, and opportunities to enhance automation, scalability, and sustainability.
- Ensure solutions continue functioning amid changes to enterprise systems, dependencies, or data availability.
- Prepare and deliver technical documentation, operational procedures, and knowledge-transfer materials for long-term maintainability.
- Communicate risks, dependencies, and technical impacts clearly and proactively to project managers, leadership, and governance groups.
Basic Qualifications - Bachelor's degree in a related field (e.g., Data Science, Computer Science, Engineering, Mathematics, Information Systems, HR Analytics, or similar).
- 8+ years of professional experience in data engineering, data science, analytics, or a closely related field.
Additional Qualifications - Extensive experience sourcing, integrating, transforming, and validating structured and unstructured data from diverse systems (e.g., developing Spark jobs, performing data manipulation with PySpark/pandas, and authoring robust, production-grade SQL transformations).
- Proven ability to design and implement automated data workflows, integration pipelines, and large-scale transformation logic (e.g., orchestrating pipelines using Apache Airflow, Azure Data Factory (ADF), or AWS Glue).
- Hands-on experience developing predictive models, statistical analyses, or machine learning solutions (e.g., building and validating models in Python using PySpark ML, pandas, or related libraries).
- Strong understanding of data quality management, validation frameworks, error-handling approaches, data governance, master data management, and enterprise metadata practices (e.g., MDM survivorship rules, identity resolution logic, validation utilizing Great Expectations).
- Demonstrated ability to facilitate requirements gathering, define business rules, and translate stakeholder needs into clear technical specifications (e.g., documenting required import fields and formats, converting business logic into ETL/ELT transformations).
- Excellent communication skills with the ability to clearly convey complex technical concepts to non-technical or cross-functional audiences (e.g., explaining data lineage, logging, and metrics practices used to ensure pipeline traceability).
- Exceptional documentation abilities and attention to detail (e.g., version-controlled artifacts in Git, CI/CD deployment documentation, and test suites using pytest and Great Expectations).
Preferred Qualifications - Master's degree preferred.
- 5+ years of experience supporting large-scale or complex data ecosystems, preferably in government, healthcare, or highly regulated domains.
- Experience supporting HR import processes for enterprise systems (e.g., HRIS, LMS, identity systems).
- Background working with federal clients or within environments that require strict attention to data standards, compliance, and documentation.
Working at ICF ICF is a global advisory and technology services provider, but we're not your typical consultants. We combine unmatched expertise with cutting-edge technology to help clients solve their most complex challenges, navigate change, and shape the future.
We can only solve the world's toughest challenges by building a workplace that allows everyone to thrive. We are an equal opportunity employer. Together, our employees are empowered to share their expertise and collaborate with others to achieve personal and professional goals. For more information, please read our EEO policy.
We will consider for employment qualified applicants with arrest and conviction records.
Reasonable Accommodations are available, including, but not limited to, for disabled veterans, individuals with disabilities, and individuals with sincerely held religious beliefs, in all phases of the application and employment process. To request an accommodation, please email and we will be happy to assist. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
Read more about workplace discrimination rights or our benefit offerings which are included in the Transparency in (Benefits) Coverage Act.
Candidate AI Usage Policy At ICF, we are committed to ensuring a fair interview process for all candidates based on their own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) tools to generate or assist with responses during interviews (whether in-person or virtual) is not permitted. This policy is in place to maintain the integrity and authenticity of the interview process.
However, we understand that some candidates may require accommodation that involves the use of AI. If such an accommodation is needed, candidates are instructed to contact us in advance at We are dedicated to providing the necessary support to ensure that all candidates have an equal opportunity to succeed.
Pay Range - There are multiple factors that are considered in determining final pay for a position, including, but not limited to, relevant work experience, skills, certifications and competencies that align to the specified role, geographic location, education and certifications as well as contract provisions regarding labor categories that are specific to the position.
The pay range for this position based on full-time employment is:
$131,256.00 - $223,134.00
Nationwide Remote Office (US99)
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