HR Data Engineer/Data 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 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 tomaintainreliable, 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 torepresentprogram needs and communicate the impact of data‑related decisions.

• Develop and execute test plans, including business‑rule 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 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, andvalidatingstructured and unstructured data from diverse systems(e.g., developing Spark jobs, performing data manipulation withPySpark/pandas, andauthoring 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.,buildingand validating models in Python usingPySparkML, 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,validationutilizingGreat 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 non‑technical or cross‑functional 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

• Master’s degree preferred.

• 5+ years of experience supportinglarge‑scaleor 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 accommodation that involves the use of AI. Ifsuch anaccommodation is needed, candidates are instructed to contact us in advance at candidateaccommodation@icf.com. Weare dedicated to providingthe necessary support to ensure that all candidates have an equal opportunity to succeed.