Data Integration Engineer

ICF•Reston, VA

1d•Remote

About The Position

This role is contingent upon a contract award. While it is not an immediate opening, we are actively conducting interviews and extending offers in anticipation of the award. The Work At ICF our Digital Modernization Division is an information technology and management consulting organization that delivers integrated, strategic solutions to federal clients. We bring expertise in cloud, cybersecurity, enterprise architecture, data modernization, and digital transformation to support mission-critical government programs. Join a team accelerating the modernization of a large federal agency's enterprise data and analytics ecosystem. This cloud-based platform provides data storage, analytics, governance, and AI/ML capabilities that enable thousands of users to transform data into actionable insights. As demand continues to grow, the team is focused on migrating legacy workloads, streamlining onboarding and support, expanding platform capabilities, and helping organizations across the enterprise adopt modern data and AI solutions at scale. The Data Integration Engineer implements data movement, replication, APIs, interoperability patterns, and source-system integration support needed to connect source systems and legacy data pathways to Summit. Coordinates secure connectivity with Platform Engineering and Security, documents approved connection patterns, and supports reliable feeds by validating performance, lineage, error handling, and operational runbooks.

Requirements

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.

Nice To Haves

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 in collaboration with Security and Platform Engineering teams.
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 for data integration platforms.
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, Event Hubs, and comparable technologies.
Experience collaborating with Data Engineers, Architects, Governance teams, Security teams, Platform Engineers, Product Owners, and operations personnel to deliver reliable and supportable integration capabilities.
Familiarity with data governance, metadata management, stewardship processes, and publication controls utilizing technologies such as Unity Catalog, Collibra EDC, Microsoft Purview, or similar solutions.
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.
Experience supporting Federal government, healthcare, or other highly regulated environments preferred.
Experience working in Agile, DevSecOps, DataOps, or cross-functional delivery teams.

Responsibilities

Implements data movement, replication, APIs, interoperability patterns, and source-system integration support needed to connect source systems and legacy data pathways to Summit.
Coordinates secure connectivity with Platform Engineering and Security, documents approved connection patterns, and supports 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 to support role delivery.
Collaborate with relevant product, engineering, security, governance, quality, and customer-facing stakeholders as required by the role.
Document work products, decisions, risks, and delivery evidence to support traceability and continuous improvement.