HR Data EngineerData Scientist

ICF isseekinga highly capableHR Data Engineer / Data Scientistto 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 requiresexpertisein 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 organizationsand can partner directly with senior stakeholders across technical and business domains.

Prior experience working infederally-regulatedenvironments and proximity to the DC-Maryland-Virginia (DMV) area with the ability to go onsite as needed is strongly preferred.

Key Responsibilities

• Design build andmaintainautomated pipelines that unify multiple HR and workforcerelated 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 semistructured data from diverse systems with varying formats and update cycles.

• Implement validation routines anomaly detection and errorhandling mechanisms tomaintainreliable highquality data products.

• Produce wellstructured standardized outputs compatible with enterprise learning or workforce management platforms.

• Collaborate with technical and nontechnical stakeholders to refine requirements resolve data ambiguities and support decisionmaking.

• Maintain alignment with enterprisewide data standards schemas and governance guidance as they evolve.

• Participate in crossteam or crossagency coordination forums torepresentprogram needs and communicate the impact of datarelated decisions.

• Develop and execute test plans including businessrule validation regression checks and iterative QA cycles.

• Identifyprocess 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 knowledgetransfer materials for longterm maintainability.

• Communicate risks dependencies and technical impacts clearly and proactively to project managers leadership and governance groups.

Basic Qualifications

• Bachelors 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 andvalidatingstructured and unstructured data from diverse systems(e.g. developing Spark jobs performing data manipulation withPySpark/pandas andauthoring robust productiongrade SQL transformations).

• Proven ability to design and implement automated data workflows integration pipelines and largescale 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.buildingand validating models in Python usingPySparkML pandas or related libraries).

• Strong understanding of data quality management validation frameworks errorhandling approaches data governance master data management and enterprise metadata practices(e.g. MDM survivorship rules identity resolution logicvalidationutilizingGreat Expectations).

• Demonstrated ability tofacilitaterequirements gathering define business rules and translate stakeholder needs into clear technical specifications(e.g. documenting requiredimport fields and formats converting business logic into ETL/ELT transformations).

• Excellent communication skills with the ability to clearly convey complex technical concepts to nontechnical or crossfunctional audiences(e.g. explaining data lineage logging andmetricspractices used to ensure pipeline traceability).

• Exceptional documentation abilities and attention to detail(e.g.version-controlled artifacts inGit CI/CD deployment documentation and test suites usingpytestand Great Expectations).

Preferred Qualifications

• Masters degree preferred.

• 5 years of experience supportinglargescaleor 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.

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 orassistwith responses during interviews (whether in-person or virtual) is notpermitted. This policy is in place tomaintainthe integrity and authenticity of the interview process.

However we understand that some candidates may require accommodationthat involves the use of AI. Ifsuch anaccommodation is needed candidates are instructed to contact us in advance at. Weare dedicated to providingthe necessary support to ensure that all candidates have an equal opportunity to succeed.