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# Data Engineer (Hybrid)

- **Company:** RTX
- **Location:** Windsor Locks, CT, United States
- **Experience:** Experienced
- **Salary:** $86,800.0 - $165,200.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Audit Trail, Microsoft Azure, Databases, Data as a Services, Data Cleansing, Data Files, Data Governance, Data Infrastructure, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Security, Data Systems, Decision Support Systems, DevOps, File Systems, Distributed Systems, Enterprise Content Management, Github, Image Management, Python (Programming Language), Machine Learning, Operational Databases, Microsoft SharePoint, SQL Databases, Unstructured Data, Apache Spark, Electronic Medical Records, Cloudformation, Pyspark, Infrastructure Automation Frameworks, Integration Frameworks, Operational Systems, Terraform, Jenkins, Databricks
- **Published:** August 15, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3354580852&tx=UT5652THT&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Typically requires a University Degree and minimum 5 years prior relevant experience or an Advanced Degree in a related field and minimum 3 years of experience.
 * Must be a U.S. Citizen.
 * Experience in engineering pipelines that handle both structured and unstructured data sources, including enterprise content repositories and file systems.
 * Demonstrated ability to segment, classify, or secure data sets based on business, legal, or compliance requirements.
 * Proficiency in Python, SQL, and data processing frameworks (Spark, PySpark, Databricks, EMR, Glue, or similar).
 * Experience with cloud platforms (AWS, Azure, or GCP) and their native data services.
 * Strong understanding of ETL/ELT, distributed systems, data modeling, and secure data architecture principles.
 * Ability to work effectively in Agile teams and collaborate across technical and business functions., * Experience designing data environments where strict security boundaries, data separation, or access controls are essential.
 * Familiarity with document processing, OCR, text extraction, image handling, or large unstructured content repositories.
 * Background with data governance, lineage, auditability, and automated policy enforcement.
 * Experience integrating data from SharePoint, network file shares, and legacy content systems.
 * Knowledge of AI/ML data preparation, feature pipelines, or working with high-sensitivity data sets.
 * Experience with DevOps and IaC tools such as Terraform, CloudFormation, GitHub Actions, or Jenkins.
 * Prior experience in aerospace, defense, manufacturing, or other regulated industries.

## Description

* Design, build, and maintain data pipelines that ingest, transform, and deliver structured data (databases, ERP/CRM systems, operational systems) and unstructured data such as file shares, SharePoint repositories, images, documents, logs, and engineering artifacts.
 * Engineer data solutions that can logically and physically segment data domains based on business rules, regulatory requirements, and security boundaries.
 * Implement strict data access controls, classification rules, and data protection mechanisms to support secure data separation across environments.
 * Build scalable architectures that support analytics, AI/ML, digital products, and data-driven decision making within sensitive or highly partitioned data landscapes.
 * Partner with cross-functional stakeholders to translate complex business and compliance requirements into reliable, secure data engineering solutions.
 * Optimize data workflows for performance, observability, and resiliency across cloud and hybrid platforms.
 * Develop reusable patterns, automation, and governance-aligned data frameworks that accelerate secure data enablement across the organization.
 * Support production data systems with strong attention to data integrity, lineage, and access auditability.

What You Will Learn:

 * How Collins business processes, systems, and data domains operate across engineering, operations, supply chain, quality, and enterprise functions.
 * Industry-specific constraints and expectations within the Aerospace & Defense sector related to data security, compliance, and controlled information.
 * How sensitive or segregated data sources-file shares, SharePoint, images, engineering documents, operational logs-flow through the business and how they must be protected.
 * How to interpret and apply business rules, legal requirements, and security considerations to design data boundaries and manage data movement responsibly.
 * Cross-functional coordination practices with program teams, cybersecurity, legal/compliance, DT, engineering, and enterprise operations, enabling tight alignment between business needs and secure data operations.


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