Data Integration Engineer

ICF

. Implement data movement, replication, APIs, interoperability patterns, and source-system integration support connecting source systems and legacy data pathways to Summit.

Posted 10/8/2026full-timeUnited StatesMid-LevelSenior💰 $81,499 - $138,549 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data integration, ETL/ELT pipeline implementation, and secure data movement across cloud and on-premises environments. Proficient in designing and supporting enterprise-scale interoperability solutions while ensuring compliance with federal requirements.

Highest-signal resume keywords

ETL/ELT Pipeline ImplementationData Integration SolutionsDatabricks and Azure Data FactoryAPI-Based Integration PatternsOperational Runbook Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IntegrationETL/ELTData ReplicationSQLPythonSparkREST APIsData ValidationData LineageMetadata Capture

Soft Skills

Analytical SkillsProblem-SolvingDecision-MakingCommunication SkillsOrganization

Tools & Technologies

DatabricksDelta LakeAzure Data FactoryMuleSoftAzure Event HubsIntegration ServicesDataOps PrinciplesCI/CD Integration

Industry Keywords

Federal Contract RequirementsLegacy Data ModernizationCloud EnvironmentsInteroperability SolutionsData Analytics Ecosystem

Tech Stack

Tools & technologies

AzureCloudETLPythonSparkSQLUnity

About the role

Key responsibilities & impact

Implement data movement, replication, APIs, interoperability patterns, and source-system integration support connecting source systems and legacy data pathways to Summit.
Coordinate secure connectivity with Platform Engineering and Security.
Document approved connection patterns.
Support reliable feeds by validating performance, lineage, error handling, and operational runbooks.
Apply data integration, APIs, replication, source-system connectivity, secure data movement, ETL/ELT, operational runbooks, and migration support.
Collaborate with product, engineering, security, governance, quality, and customer-facing stakeholders.
Document work products, decisions, risks, and delivery evidence to support traceability and continuous improvement.
Support modernization of a federal agency's enterprise data and analytics ecosystem, including migration of legacy workloads, onboarding, platform support, and adoption of modern data and AI solutions.

Requirements

What you’ll need

U.S. Citizenship is required due to federal contract requirements.
Candidate must reside in the U.S., be authorized to work in the U.S., and all work must be performed in the U.S.
Candidate must have lived in the U.S. for three (3) full years out of the last five (5) years.
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Database Administration, Systems Engineering, Cloud Engineering, or related field; or a high school diploma with four (4) additional years of relevant experience in lieu of a bachelor's degree.
Minimum 6 years of relevant experience aligned to the responsibilities of this role.
Master's degree may substitute for two (2) years of relevant experience.
Experience designing, implementing, and supporting enterprise-scale data integration, interoperability, and data movement solutions across cloud, hybrid, and on-premises environments.
Strong experience implementing ETL/ELT pipelines, data replication strategies, ingestion frameworks, and migration solutions utilizing Databricks, Delta Lake, Azure Data Factory, Spark, SQL, and Python.
Experience supporting large-scale legacy data warehouse modernization and migration initiatives, including data validation, reconciliation, and migration cutover activities.
Experience designing and implementing API-based, event-driven, batch, and streaming integration patterns utilizing REST APIs, MuleSoft, Azure Event Hubs, messaging frameworks, or comparable technologies.
Experience implementing secure data exchange, data-sharing, and interoperability solutions across multiple platforms, business domains, and cloud environments.
Experience with Databricks Lakehouse architecture, Delta Sharing, Lakehouse Federation, Unity Catalog, and modern data-sharing frameworks.
Experience integrating structured, semi-structured, and unstructured data sources into enterprise analytics platforms.
Experience implementing secure connectivity patterns, network integration controls, identity management, and access governance.
Experience developing and maintaining operational runbooks, integration standards, connection patterns, support documentation, and troubleshooting procedures.
Experience implementing data lineage, metadata capture, monitoring, observability, alerting, and operational telemetry.
Experience validating integration performance, throughput, latency, reliability, error handling, exception management, and operational readiness.
Experience supporting cloud-native integration platforms and services including Azure Data Factory, Azure Integration Services, Databricks Workflows, APIs, and Event Hubs.
Strong programming and scripting skills utilizing SQL, Python, Spark, REST APIs, JSON, and data integration frameworks.
Understanding of DataOps principles, automated testing, pipeline validation, deployment automation, and CI/CD integration patterns.
Highly effective analytical, problem-solving, and decision-making capabilities.
Excellent written and verbal communication skills.
Strong organization, attention to detail, and ability to manage multiple responsibilities.

Benefits

Comp & perks

Equal opportunity employer
Reasonable accommodations for disabled veterans, individuals with disabilities, and individuals with sincerely held religious beliefs
Accommodation support for disability or religious purposes during the application process