Design, build, and maintain scalable data pipelines that support batch and real-time data processing across structured and unstructured data sources.
Develop and optimize ETL/ELT workflows to ensure efficient data ingestion, transformation, and delivery into data warehouses, data lakes, or lakehouse environments.
Collaborate closely with data architecture, analytics, ML engineering, and product teams to understand data requirements and translate them into reliable technical solutions.
Implement data quality checks, data validation logic, and automated monitoring to ensure accuracy, completeness, and reliability of datasets.
Work with cloud platforms (e.g., Azure and AWS) and distributed computing frameworks (e.g., Spark) to build high-performance data systems.
Design and maintain metadata, lineage, and documentation that provides transparency into the data lifecycle and supports governance & compliance needs.
Optimize data storage, compute, and pipeline performance to reduce cost and increase efficiency.
Implement security and access control standards for sensitive data in alignment with organizational policies and compliance regulations.
Troubleshoot production data issues, perform root cause analysis, and drive permanent fixes rather than temporary workarounds.
Continuously evaluate new tools, technologies, and patterns to improve data engineering capabilities and align with future scalability requirements.

Requirements

Bachelor’s degree in a STEM discipline with 5+ years of professional experience in data engineering, software engineering, or a similar role, with a strong focus on building and maintaining robust data pipelines.
5+ years in programming languages, particularly Python, for building and automating data pipelines and analytics data stores.
Experience with Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) processes and tools like Matillion or other replication tool like HVR (Fivetran) or QLIK Replicate.
3+ years relevant experience with cloud computing platforms (AWS and/or Azure).
Knowledge of data warehousing concepts, data modeling, and schema design.
Understanding of data governance, lineage, quality frameworks, and metadata management.
Must be authorized to work in the U.S. without sponsorship now or in the future. RTX will not offer sponsorship for this position.
25% travel required within USA.

Benefits

Obtain professional certificates and degrees through the RTX employee scholar program.
Comprehensive benefits package, including medical, dental, vision, life, short term disability, and long term disability benefits.
Paid time off including holidays, sick time, and parental leave.
401(k) with matching.
Rotational programs.
Reward and recognition programs.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

data pipelinesETLELTPythondata warehousingdata modelingschema designdata quality checksdata validationroot cause analysis

collaborationproblem solvingcommunicationorganizational skillsattention to detail