Lead Data/ETL Engineer

DecisionPoint | Cortek•Chicago, IL

2h•Remote

About The Position

DecisionPoint seeks a Lead Data/ETL Engineer to provide technical leadership and hands-on engineering for data ingestion, transformation, integration, and delivery under the USMEPCOM ENLIST program. This SME-level role maintains and optimizes SQL Server Integration Services (SSIS), implements approved API integrations and incremental loading approaches, and builds raw, standardized, and curated data layers. The engineer establishes reliable processes for reconciliation, retries, schema changes, identifier mappings, lineage, and failed-record handling. The role collaborates with database administrators, architects, governance personnel, AI/ML engineers, BI developers, testers, and Government stakeholders to deliver accurate, traceable, and maintainable data pipelines supporting mission analysis, AI capabilities, and reporting. The position is remote, with Chicago-area candidates preferred. Applicants acknowledge and consent to having their resume included in an active competitive government contract bid.

Requirements

Active Secret clearance or higher.
Minimum of 12 years of relevant professional experience.
Bachelor’s degree in computer science, information systems, or a related field, or a permitted equivalent.
Experience maintaining and optimizing SQL Server Integration Services (SSIS).
Strong SQL skills.
Experience with Python and data engineering automation.
Experience implementing and supporting API integrations.
Experience developing incremental data loads.
Experience documenting and maintaining data lineage.
Experience troubleshooting complex data pipelines.
Ability to build raw, standardized, and curated data layers.
Ability to manage reconciliation, retries, schema changes, identifier mappings, and failed-record handling.
Ability to implement change-data capture where appropriate.
CompTIA Security+ CE or another approved IAT Level II certification when applicable to assigned duties.

Nice To Haves

Relevant data engineering or cloud platform certification.
Experience supporting federal or Department of Defense data environments.
Experience modernizing legacy SSIS integrations or transitioning pipelines to approved cloud platforms.
Experience with enterprise data warehouses, analytical datasets, BI platforms, or AI-ready data.
Familiarity with data catalogs, metadata management, data governance, and automated lineage tools.
Experience developing automated data-quality checks, reconciliation frameworks, and pipeline regression tests.
Experience integrating data engineering workflows with CI/CD, version control, and automated deployment.
Experience implementing secure service accounts, secrets management, encryption, and pipeline audit logging.
Strong technical mentoring, documentation, troubleshooting, and stakeholder communication skills.

Responsibilities

Lead the design, implementation, maintenance, and optimization of enterprise data integration and ETL pipelines.
Maintain and optimize SSIS packages, configurations, schedules, dependencies, and execution processes.
Develop SQL queries, stored procedures, transformations, and reconciliation logic.
Use Python or another approved automation language to support ingestion, orchestration, validation, monitoring, and recovery.
Implement approved API integrations, including authentication, pagination, rate-limit handling, retries, and error processing.
Design incremental loading strategies and implement change-data capture where appropriate and approved.
Build and maintain raw, standardized, and curated data layers with documented transformation rules.
Establish source-to-target mappings, common identifier mappings, and consistent handling of reference data.
Implement reconciliation checks to verify record counts, totals, completeness, and transformation accuracy.
Develop restartable processing, controlled retries, checkpoints, and recovery procedures.
Implement failed-record handling, quarantine processes, error logging, and controlled reprocessing.
Assess and manage schema changes and their effects on pipelines, datasets, analytical models, and reports.
Maintain data lineage, transformation documentation, interface specifications, and pipeline dependencies.
Monitor pipeline execution, throughput, freshness, resource utilization, and operational failures.
Troubleshoot complex issues involving source systems, APIs, SSIS packages, SQL logic, data quality, and downstream integrations.
Optimize pipeline performance while maintaining data integrity, traceability, and approved security controls.
Coordinate with governance personnel on definitions, ownership, authoritative sources, metadata, and approved data uses.
Work with independent testing personnel to support reconciliation, regression testing, defect resolution, and release validation.
Coordinate pipeline changes with database, application, AI/ML, warehouse, and BI teams.
Maintain version-controlled code, deployment instructions, rollback procedures, and operational runbooks.
Review technical designs and code, guide engineering practices, and provide knowledge transfer to other engineers.
Communicate pipeline health, risks, dependencies, corrective actions, and improvement recommendations to technical leads and Government stakeholders.