Data Integration Engineer, 2 yrs exp

Jobtailor; Washington (District of Columbia); On-site; USD 90,000 - 130,000; Full time

Job summary

Jobtailor is seeking a data integration professional to support end-to-end data movement across OneStream, ERP systems, and reporting platforms in Washington, DC. You will design, validate, and optimize batch and API-based data flows, ensuring data accuracy, timeliness, and traceability through source-to-target validations and reconciliations.

The role requires 2+ years of relevant experience, a STEM degree, and familiarity with cloud platforms (Azure, AWS, Databricks).

Qualifications

• 2+ years of professional experience supporting enterprise data integration, financial systems, ERP modernization, cloud data engineering, software development, or related technical initiatives.
• Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, Computer Engineering, Information Technology, or another STEM discipline.
• Experience or academic/project experience developing or supporting APIs, ETL/ELT pipelines, batch processing, file-based integrations, or middleware platforms.
• Working knowledge of SQL with experience querying, validating, and analyzing datasets.
• Experience or familiarity with source-to-target validation, data reconciliation, and enterprise data quality analysis.
• Experience supporting or participating in System Integration Testing (SIT), User Acceptance Testing (UAT), production deployments, and post-production support.
• Foundational 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.
• Ability to manage multiple priorities within a fast-paced consulting environment.
• U.S. citizenship with the ability to obtain and maintain a security clearance.

Responsibilities

• Support the design, development, configuration, testing, and maintenance of enterprise data integrations supporting OneStream, ERP platforms, and financial reporting systems.
• Assist with defining integration requirements, interface controls, source-to-target mappings, transformation logic, and validation criteria.
• Support the development, testing, and validation of 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.
• Assist in executing 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 working with senior engineers to implement 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.

Skills

SQL Proficiency

Analytical Skills

Troubleshooting

Time Management

Collaboration

Education

Bachelor's degree in a STEM discipline

Tools

OneStream

ERP Platforms

Azure

AWS

Databricks

Middleware Platforms

Job description

• Support the design, development, configuration, testing, and maintenance of enterprise data integrations supporting OneStream, ERP platforms, and financial reporting systems.
• Assist with defining integration requirements, interface controls, source-to-target mappings, transformation logic, and validation criteria.
• Support the development, testing, and validation of 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.
• Assist in executing 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 working with senior engineers to implement 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.

Requirements

• 2+ years of professional experience supporting enterprise data integration, financial systems, ERP modernization, cloud data engineering, software development, or related technical initiatives.
• Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, Computer Engineering, Information Technology, or another STEM discipline.
• Experience or academic/project experience developing or supporting APIs, ETL/ELT pipelines, batch processing, file-based integrations, or middleware platforms.
• Working knowledge of SQL with experience querying, validating, and analyzing datasets.
• Experience or familiarity with source-to-target validation, data reconciliation, and enterprise data quality analysis.
• Experience supporting or participating in System Integration Testing (SIT), User Acceptance Testing (UAT), production deployments, and post-production support.
• Foundational 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.
• 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 expertise in enterprise data integration, including API development, ETL/ELT pipeline support, and data reconciliation. Proficient in SQL for data validation and analysis, with a strong focus on ensuring data quality and integrity across financial systems.

Highest-signal resume keywords

• Enterprise Data Integration
• API Development
• ETL/ELT Pipeline Support
• SQL Proficiency
• Data Reconciliation

ATS Optimization Keywords

Hard Skills

• Data Integration
• API Development
• ETL
• ELT
• SQL
• Data Mapping
• Data Transformation
• Data Validation
• Data Quality Analysis
• Batch Processing

Soft Skills

• Analytical Skills
• Troubleshooting
• Root-Cause Analysis
• Time Management
• Collaboration

Industry Keywords

• Financial Reporting Systems
• System Integration Testing
• User Acceptance Testing
• Data Movement Processes
• Enterprise Data Quality

Tools & Technologies

• OneStream
• ERP Platforms
• Cloud Data Platforms
• Azure
• AWS
• Databricks
• Middleware Platforms