Senior Data Integration Engineer

Jobtailor

Washington (District of Columbia)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Jobtailor is seeking an experienced data integration professional in Washington, DC to design, implement, and validate enterprise data interfaces across ERP and financial reporting systems. You will refine requirements, build batch and API integrations, and ensure end-to-end data accuracy and timeliness.

The role involves three-way reconciliations, troubleshooting, and post-deployment support while collaborating with finance, data engineers, and business stakeholders.

Qualifications

10+ years of experience supporting enterprise data integration, financial systems, ERP modernization, or cloud data engineering initiatives.
Experience developing or supporting APIs, ETL/ELT pipelines, batch processing, file-based integrations, or middleware platforms.
Strong SQL skills with experience querying, validating, and reconciling large datasets.
Experience performing source-to-target validation, data reconciliation, and enterprise data quality analysis.
Experience supporting System Integration Testing (SIT), User Acceptance Testing (UAT), production deployments, and post-production support.
Understanding of enterprise integration patterns, data mapping, transformation logic, and interface controls.
Familiarity with cloud-based data platforms such as Azure, AWS, or Databricks.
Excellent communication skills with the ability to collaborate across technical and business teams.
U.S. citizenship with the ability to obtain and maintain a security clearance.

Responsibilities

Design, develop, configure, and support enterprise data integrations supporting OneStream, ERP platforms, and financial reporting systems.
Support definition of integration requirements, interface controls, source-to-target mappings, transformation logic, and validation criteria.
Develop and validate batch integrations, APIs, file transfers, ETL/ELT pipelines, and cloud-based data movement processes.
Validate end-to-end data movement across source systems, staging environments, transformation layers, enterprise data platforms, and downstream reporting solutions.
Perform source-to-target validation to verify data completeness, accuracy, timeliness, and traceability.
Execute three-way reconciliations between source systems, transformed datasets, and reporting platforms to identify and resolve data discrepancies.
Troubleshoot interface failures, schema changes, mapping defects, rejected records, transformation errors, and data processing exceptions while documenting root causes and coordinating resolutions.
Support synchronization of master data, reference data, metadata, mappings, and key business attributes for reliable reporting.
Support SIT, UAT, cutover validation, production deployments, and post-implementation stabilization activities.
Collaborate with developers, data engineers, finance orgs, source system owners, and stakeholders to improve interface reliability.
Develop interface specifications, mapping documents, reconciliation procedures, runbooks, and technical documentation.
Support ERP modernization initiatives, historical data conversions, and production cutovers.
Monitor production interfaces and identify opportunities to improve automation, performance, and resilience.
Utilize Power BI, Databricks, Palantir, Celonis Intelligence, SQL, and Python to analyze enterprise data, develop dashboards, and support data quality initiatives.
Leverage AI-assisted analytics to automate reconciliation and anomaly detection.

Skills

Enterprise Data Integration

SQL Proficiency

ETL/ELT Pipeline Development

System Integration Testing (SIT)

Cloud Data Platforms

Analytical Skills

Troubleshooting

Root-Cause Analysis

Communication Skills

Collaboration

Education

Bachelor's degree in STEM

Tools

Power BI

Databricks

Palantir

Celonis Intelligence

Azure

AWS

Middleware Platforms

Job description

Design, develop, configure, and support enterprise data integrations supporting OneStream, ERP platforms, and financial reporting systems.
Support definition of integration requirements, interface controls, source-to-target mappings, transformation logic, and validation criteria.
Develop and validate batch integrations, APIs, file transfers, ETL/ELT pipelines, and cloud-based data movement processes.
Validate end-to-end data movement across source systems, staging environments, transformation layers, enterprise data platforms, and downstream reporting solutions.
Perform source-to-target validation to verify the completeness, accuracy, timeliness, and traceability of financial and operational data.
Execute three-way reconciliations between source systems, transformed datasets, and reporting platforms to identify and resolve data discrepancies.
Troubleshoot interface failures, schema changes, mapping defects, rejected records, transformation errors, and data processing exceptions while documenting root causes and coordinating technical resolutions.
Support synchronization of master data, reference data, metadata, mappings, and key business attributes required for reliable enterprise reporting.
Support System Integration Testing (SIT), User Acceptance Testing (UAT), cutover validation, production deployments, and post-implementation stabilization activities.
Collaborate with software developers, data engineers, finance organizations, source system owners, and business stakeholders to improve interface reliability and reduce manual processing.
Develop interface specifications, mapping documents, reconciliation procedures, operational runbooks, and technical documentation.
Support ERP modernization initiatives, enterprise system implementations, historical data conversions, and production cutovers.
Monitor production interfaces and proactively identify opportunities to improve automation, performance, scalability, and operational resilience.
Utilize Power BI, Databricks, Palantir, Celonis Intelligence, SQL, and Python to analyze enterprise data, develop dashboards, and support data quality initiatives.
Leverage AI-assisted analytics and agentic AI technologies to automate reconciliation, anomaly detection, interface monitoring, and operational support.
Prepare technical documentation, executive briefings, and client deliverables supporting project leadership and decision-making.

Requirements

10+ years of experience supporting enterprise data integration, financial systems, ERP modernization, or cloud data engineering initiatives.
Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, Computer Engineering, Information Technology, or another STEM discipline.
Experience developing or supporting APIs, ETL/ELT pipelines, batch processing, file-based integrations, or middleware platforms.
Strong SQL skills with experience querying, validating, and reconciling large datasets.
Experience performing source-to-target validation, data reconciliation, and enterprise data quality analysis.
Experience supporting System Integration Testing (SIT), User Acceptance Testing (UAT), production deployments, and post-production support.
Understanding of enterprise integration patterns, data mapping, transformation logic, and interface controls.
Familiarity with cloud-based data platforms such as Azure, AWS, or Databricks.
Strong analytical, troubleshooting, and root-cause analysis skills.
Excellent communication skills with the ability to collaborate across technical and business teams.
Ability to manage multiple priorities within a fast-paced consulting environment.
U.S. citizenship with the ability to obtain and maintain a security clearance.

Core Competencies

Demonstrates extensive experience in enterprise data integration, financial systems, and cloud data engineering, with a strong focus on SQL, ETL/ELT pipelines, and data reconciliation. Proven ability to collaborate with cross-functional teams and support system integration testing and production deployments.

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