Data/ETL Engineer (Senior)

DecisionPoint | Cortek•Chicago, IL

6h•Remote

About The Position

DecisionPoint seeks a Senior Data/ETL Engineer to sustain SQL Server Integration Services (SSIS), develop approved integrations, and maintain reliable data pipelines supporting the USMEPCOM ENLIST program. The engineer will implement raw, standardized, and curated data layers using SQL, Python, APIs, and incremental loading techniques. Responsibilities also include reconciling data, managing schema changes, maintaining lineage, and troubleshooting complex pipeline failures to support accurate and timely mission analysis, AI capabilities, and reporting. The Senior Data/ETL Engineer will work with the Lead Data/ETL Engineer, database administrators, data governance personnel, AI/ML engineers, BI developers, testers, and Government stakeholders to maintain secure, traceable, and supportable data integrations. 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 eight years of relevant professional experience.
Bachelor’s degree in computer science, information systems, or a related field, or a permitted equivalent.
Experience maintaining and supporting SQL Server Integration Services (SSIS).
Strong SQL and Python skills.
Experience building or supporting API integrations.
Experience implementing incremental data loads.
Experience performing data reconciliation and managing schema changes.
Experience documenting and maintaining data lineage.
Experience troubleshooting complex data pipelines.
Ability to implement raw, standardized, and curated data layers.
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 with enterprise data warehouses, analytical datasets, BI platforms, or AI-ready data.
Experience modernizing SSIS packages or migrating integrations to approved cloud services.
Familiarity with data governance, metadata repositories, common identifiers, and authoritative sources.
Experience developing automated reconciliation tests, data-quality checks, and pipeline regression tests.
Experience with CI/CD, version control, automated deployment, and rollback processes.
Familiarity with secure service accounts, secrets management, encryption, and audit logging.
Strong troubleshooting, documentation, communication, and cross-team coordination skills.

Responsibilities

Sustain, troubleshoot, and optimize SSIS packages, configurations, schedules, and dependencies.
Develop and maintain approved integrations between source systems, databases, APIs, analytical environments, and reporting platforms.
Write SQL queries, stored procedures, transformations, and reconciliation routines.
Develop Python scripts for data ingestion, processing, validation, orchestration, and operational automation.
Implement raw, standardized, and curated data layers with documented transformation rules.
Build and maintain incremental loads, including checkpoints and tracking of previously processed data.
Implement API authentication, pagination, retry handling, logging, and error processing.
Reconcile source and target data using record counts, totals, completeness checks, and business rules.
Manage schema changes and assess their effects on pipelines, datasets, integrations, and reporting outputs.
Maintain source-to-target mappings, identifier mappings, metadata, and data lineage.
Implement controls for duplicate, missing, invalid, or failed records and support controlled reprocessing.
Monitor pipeline execution, data freshness, processing performance, and operational errors.
Investigate complex failures involving SSIS, SQL, APIs, source data, transformations, and downstream dependencies.
Implement approved corrections and validate successful processing and reconciliation.
Coordinate changes with database, application, governance, AI/ML, BI, and testing teams.
Support automated regression testing, data-quality checks, defect resolution, and release validation.
Maintain version-controlled code, deployment instructions, rollback procedures, and operational runbooks.
Provide technical status, troubleshooting findings, risks, and improvement recommendations to the technical lead and Government stakeholders.