Eng Sr - HW

BAE Systems•Endicott, NY

8d•Onsite

About The Position

Works closely with engineering and program teams to provide technical leadership in reliability analysis, identify product performance trends, and drive continuous improvement across design, manufacturing, and support environments. The role maintains and codes databases that track production and in‑service performance of both commercial and military aerospace and transportation platforms, and collaborates with the Product Support/ILS Engineering Unit on reliability predictions, electrical‑stress and derating analysis, provisioning‑T‑file analysis, maintainability analysis, and the generation of technical publications.

Requirements

Bachelor’s degree in Electrical, Mechanical, Systems Engineering, or related technical field.
Minimum of 5 years in reliability, maintainability, or supportability engineering; 10 years for senior roles.
Experience with ISO‑9001, ISO 14224, EN 497, IEC 61508, or similar standards.
Proven track record of using statistical tools (Weibull analysis, Pareto charts, MTBF/MTBUR modeling) and advanced Excel or equivalent analytical software.
Familiarity with relational databases (Oracle, TOAD, BART, MIDAS) and modern cloud‑based analytics platforms (AWS, Azure).
Strong understanding of electronic components, circuits, and interfaces; ability to rapidly learn customer web‑based applications for data mining and reporting.
Ability to model failure distributions, conduct (F)MECAs, and leverage machine‑learning algorithms for predictive reliability.
Excellent verbal and written communication, capable of producing technical publications, proposals, and presenting data to diverse audiences.
Skilled at coordinating and negotiating with company personnel, customers, and suppliers; adept at leading cross‑functional teams.
Use sound judgment while complying with relevant policies, regulations, and laws.
Strict attention to detail, robust documentation, and commitment to process compliance (ISO‑9001, ISO 14224).

Nice To Haves

BSEE +10 years of experience in In-Service Reliability or related engineering disciplines.
Advanced degree in Reliability Engineering, Systems Engineering, or a related discipline.
Experience applying Lean Six Sigma tools to reliability projects.
Demonstrated ability to automate reliability analysis workflows using Python/R, Power‑BI, or equivalent tools.
Familiarity with ISO 14224 data structures and exchange protocols, and with cyber‑reliability frameworks.
Familiarity with Weibul Analysis and ability to model distributions using Weibul tools
Ability to recommend design changes for Reliability Improvement

Responsibilities

Manage the end‑to‑end production of all reliability program analysis documents.
Review RFPs/RFQs to determine reliability requirements; provide inputs for cost and logistics projections.
Proactively lead relationships with internal and external stakeholders to secure program opportunities and ensure alignment with customer expectations.
Oversee budgets, schedules, and cost‑accounting for supportability and logistics tasks; develop and maintain support and services plans for all supported programs.
Lead system‑design discussions focusing on logistics innovations that reduce Life‑Cycle Cost (LCC) and Total Ownership Cost (TOC).
Develop and review PSA, LPD, LCC, LORA, and support‑system trade‑off analyses; ensure Engineering Change Proposals (ECPs) address total logistics impact.
Continuously improve reliability processes, ensuring compliance with ISO‑9001 and emerging standards such as ISO 14224, EN 497, and IEC 61508.
Assess reliability impact of cyber‑threats and functional safety concerns; coordinate with cybersecurity teams to embed resilience in design.
Lead the adoption of Python/R, SQL, Power BI, and automated failure‑mode tools to mine telemetry, build predictive models, and generate real‑time dashboards.
Apply DMAIC methodology to root‑cause analyses, reduce MTBF improvements, and lower operational costs.
Encourage pursuit of industry certifications (CRE, CRL) and continuous learning in emerging reliability domains.