Data Integration Engineer

ICF • Reston, AL

2d • $81,499 - $138,549 • Remote

About The Position

The Data Integration Engineer supports modernization of a large federal agency’s enterprise data and analytics ecosystem. The role implements data movement, replication, APIs, interoperability patterns, and source-system integration to connect source systems and legacy data pathways to Summit, a cloud-based platform for data storage, analytics, governance, and AI/ML capabilities. The engineer coordinates secure connectivity with Platform Engineering and Security, documents approved connection patterns, and helps ensure reliable data feeds by validating performance, lineage, error handling, and operational runbooks.

The position is remote, with a strong preference for candidates in the Washington, DC Metro Area and occasional onsite meetings at the client site in Washington, DC. The role is contingent upon a contract award; interviews and offers are being conducted in anticipation of the award. All work must be performed in the United States, and the employer monitors work locations, blocks access from foreign locations or IP addresses, and prohibits personal VPN connections.

Requirements

• 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, Information Systems, Database Administration, Systems Engineering, Cloud Engineering, or a related field; alternatively, a high school diploma plus four additional years of relevant experience may substitute for a bachelor’s degree.
• At least 6 years of relevant experience aligned to the role’s responsibilities.
• A master’s degree may substitute for two years of relevant experience.
• Highly effective analytical, problem-solving, and decision-making capabilities.
• Excellent written and verbal communication skills, with the ability to work effectively with technical and non-technical audiences.
• Strong organization, attention to detail, and ability to prioritize and manage multiple responsibilities.
• Collaborative approach and commitment to quality, accountability, and continuous improvement.

Nice To Haves

• Experience designing, implementing, and supporting enterprise-scale data integration, interoperability, and data movement solutions across cloud, hybrid, and on-premises environments.
• Experience implementing ETL/ELT pipelines, data replication strategies, ingestion frameworks, and migration solutions using Databricks, Delta Lake, Azure Data Factory, Spark, SQL, and Python.
• Experience supporting large-scale legacy data warehouse modernization and migration, including data validation, reconciliation, and migration cutover activities.
• Experience designing and implementing API-based, event-driven, batch, and streaming integration patterns using REST APIs, MuleSoft, Azure Event Hubs, messaging frameworks, or comparable technologies.
• Experience implementing secure data exchange, data-sharing, and interoperability solutions across 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 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 such as Azure Data Factory, Azure Integration Services, Databricks Workflows, APIs, and Event Hubs.
• Experience collaborating with Data Engineers, Architects, Governance teams, Security teams, Platform Engineers, Product Owners, and operations personnel.
• Familiarity with data governance, metadata management, stewardship processes, and publication controls using Unity Catalog, Collibra EDC, Microsoft Purview, or similar solutions.
• Strong programming and scripting skills using 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.
• Experience working in Agile, DevSecOps, DataOps, or cross-functional delivery teams.

Responsibilities

• Implement data movement, replication, APIs, interoperability patterns, and source-system integration to connect source systems and legacy data pathways to Summit.
• Coordinate secure connectivity with Platform Engineering and Security, document approved connection patterns, and 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 to deliver the role’s work.
• Collaborate with product, engineering, security, governance, quality, and customer-facing stakeholders as required.
• Document work products, decisions, risks, and delivery evidence to support traceability and continuous improvement.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level