Senior Data Automation and Integration Engineer

International Logic Systems, Inc.•Fairfax, VA

6h•Hybrid

About The Position

International Logic Systems (ILS) is seeking a Senior Data Automation and Integration Engineer to design, automate, and support secure data workflows that acquire, transform, validate, store, and deliver reliable data for analytics and reporting. The ideal candidate will partner with business and technology teams to build reusable and scalable data solutions, troubleshoot data and integration issues, and ensure compliance with established security, data governance, and data quality standards. This is a hybrid position requiring on-site presence two days per week at the ILS headquarters in Fairfax, VA 22033. Candidates must be local to the DC Metro area and able to commute to the Fairfax, VA office two days per week.

Requirements

Bachelor’s degree and 5 years of relevant experience.
Hands-on experience with workflow orchestration, PowerShell, Python, SQL, and ETL/ELT.
Experience with relational databases, data modeling, data quality, monitoring, and failure recovery.
Knowledge of business intelligence, security, data governance, and change-control practices.
Strong troubleshooting, documentation, communication, and stakeholder-management skills.
Ability to work independently in Agile or hybrid delivery environments.

Nice To Haves

Experience with cloud data platforms, object storage, low-code automation, or deployment pipelines.
Knowledge of identity and access management, privacy or compliance controls, and advanced analytics.
Relevant cloud, data, automation, cybersecurity, or business intelligence certifications.

Responsibilities

Design secure, maintainable data architectures using approved cloud, database, analytics, and identity technologies.
Document system components, interfaces, data flows, security boundaries, and access patterns.
Coordinate configuration, connectivity, and dependencies with technology and application teams.
Build and maintain automated data pipelines across approved internal and external sources.
Use workflow orchestration, scripting, SQL, and automation tools to schedule, process, and monitor data.
Develop reusable ingestion, transformation, validation, and storage patterns.
Partner with data owners to understand source structures, business rules, refresh cycles, quality issues, and privacy requirements.
Ensure retention, access, and handling practices align with data-governance standards.
Implement validation, reconciliation, logging, alerting, and recovery controls.
Investigate data-quality issues, pipeline failures, and service interruptions; coordinate resolution with stakeholders.
Maintain runbooks and troubleshooting procedures for reliable operations and support.
Prepare trusted, reusable datasets for dashboards, reports, search, metrics, and self-service analysis.
Define data models, relationships, calculations, refresh requirements, validation criteria, and traceability with analysts.
Assess data sources, tools, infrastructure, access, and operational gaps.