Data Validation Engineer

ICF

. Implement technical controls for data parity, freshness, anomaly detection, pipeline observability, alerting, defect tracking, and release evidence .

Posted 10/8/2026full-timeUnited StatesMid-LevelSenior💰 $98,614 - $167,644 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in implementing automated data quality controls, anomaly detection, and pipeline observability within cloud-based data ecosystems. Proficient in collaborating with cross-functional teams to ensure data integrity and compliance in highly regulated environments.

Highest-signal resume keywords

Automated Data Quality ControlsData Freshness MonitoringDatabricks ExpertiseDataOps PracticesData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonSparkData Quality AutomationAnomaly DetectionData LineageDefect TrackingStatistical ValidationETL/ELT Pipeline MonitoringMetadata Management

Soft Skills

Analytical SkillsProblem-SolvingDecision-MakingCommunication SkillsOrganization

Tools & Technologies

DatabricksDelta LakeAzure Data FactoryUnity CatalogCollibra EDCMicrosoft PurviewGitHub ActionsAzure DevOpsTerraformGreat Expectations

Industry Keywords

Data GovernanceData StewardshipPublication Approval ProcessesFederal GovernmentHealthcare

Tech Stack

Tools & technologies

AzureCloudETLPythonSparkSQLTerraformUnity

About the role

Key responsibilities & impact

Implement technical controls for data parity, freshness, anomaly detection, pipeline observability, alerting, defect tracking, and release evidence
Wire pipelines to monitoring and reporting mechanisms so data quality problems are detected and acted upon before customer release
Work with Governance on rule libraries, Definitions of Done, quality thresholds, and publication gates
Apply data quality automation, parity testing, freshness SLAs, anomaly detection, pipeline observability, alerting, data lineage, and defect tracking
Collaborate with product, engineering, security, governance, quality, and customer-facing stakeholders
Document work products, decisions, risks, and delivery evidence for traceability and continuous improvement
Support modernization of a federal agency's cloud-based enterprise data and analytics ecosystem

Requirements

What you’ll need

U.S. Citizenship is required due to federal contract requirements
Must reside in the U.S., be authorized to work in the U.S., and perform all work in the U.S.
Must have lived in the U.S. for three full years out of the last five years
Bachelor's degree in Computer Science, Data Engineering, Data Quality Engineering, Information Systems, Statistics, Applied Mathematics, Software Engineering, or related field; or a high school diploma with four additional years of relevant experience in lieu of a bachelor's degree
Minimum 6 years of relevant experience aligned to the role responsibilities
Master's degree may substitute for two years of relevant experience
Experience designing and implementing automated data quality, data validation, and data observability frameworks in cloud-based data and analytics platforms
Experience with automated data quality controls, reconciliation processes, parity testing frameworks, and release validation mechanisms
Experience with data freshness monitoring, SLAs, data certification workflows, and publication readiness controls
Experience with anomaly detection, drift detection, statistical validation, and exception monitoring across structured, semi-structured, and analytical datasets
Expertise with Databricks, Delta Lake, Delta Live Tables, SQL, Python, Spark, and modern Lakehouse architectures
Experience with medallion architecture layers, data pipelines, data products, reporting layers, and published analytical assets
Experience with Great Expectations, Soda, Monte Carlo, Databricks Expectations, Deequ, or comparable technologies
Experience monitoring and validating ETL/ELT pipelines, Azure Data Factory workflows, Spark jobs, Databricks Workflows, APIs, streaming pipelines, and enterprise integrations
Experience with metadata management, data lineage, governance controls, and publication certification using Unity Catalog, Collibra EDC, Microsoft Purview, or similar technologies
Experience developing automated alerting, defect detection, operational dashboards, issue triage processes, and quality metrics
Experience implementing DataOps practices, pipeline observability, operational telemetry, root-cause analysis, error classification, and automated remediation patterns
Experience supporting AI/ML and analytics workloads through training-data validation, feature quality monitoring, model-input validation, model-output verification, drift monitoring, explainability assessments, and AI quality controls
Familiarity with MLOps, MLflow, Azure Machine Learning, Databricks ML, model lifecycle management, and production AI governance
Experience developing release evidence, validation reports, audit artifacts, quality scorecards, and engineering controls
Experience collaborating with Data Governance Leads, Data Quality Analysts, Data Engineers, AI Engineers, Product Owners, Architects, QA teams, and Platform Engineers
Experience with test automation and validation controls in CI/CD and DataOps pipelines using GitHub Actions, Azure DevOps, Terraform, or equivalent platforms
Strong understanding of data governance, data stewardship, lineage, metadata management, and publication approval processes
Experience supporting federal government, healthcare, or other highly regulated environments preferred
Experience in Agile, DevSecOps, DataOps, or cross-functional delivery teams
Highly effective analytical, problem-solving, and decision-making capabilities
Excellent written and verbal communication skills across technical and non-technical audiences
Strong organization, attention to detail, prioritization, and multitasking abilities

Benefits

Comp & perks

Remote work arrangement
Occasional onsite meetings on the client site in Washington, DC
Reasonable accommodations for disabilities, disabled veterans, and sincerely held religious beliefs
Equal opportunity employment