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Sr Analytics Engineer
Job in
Springdale, Hamilton County, Ohio, USA
Listed on 2026-01-01
Listing for:
GE Aerospace
Full Time
position Listed on 2026-01-01
Job specializations:
-
IT/Tech
Data Analyst, Data Engineer
Job Description & How to Apply Below
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Job Description SummaryThe Senior Analytics Engineer designs, builds, and scales analytics that improve Safety, Quality, Delivery, and Cost (SQDC) for the Aviation Component Service Center (ACSC) in Springdale, OH. You will own the end‑to‑end analytics lifecycle—from partnering with shop leaders and process owners to developing & maintaining data pipelines, models, and Spotfire dashboards that power daily management, root‑cause problem solving, and continuous improvement on the shop floor.
This role combines deep data engineering expertise with a strong inclination to develop business acumen and a bias for action.
- End‑to‑End Ownership:
Lead the full analytics lifecycle—requirements gathering, data acquisition, pipeline development, modelling, visualization, and user enablement—to deliver actionable insights for ACSC engine component repair operations. - Data Pipeline Development:
Design, build, and maintain reliable ETL/ELT pipelines ingesting data from ERP/MES/QMS, test/inspection, and manual logs; ensure repeatability, observability, and resilience. - Data Modeling:
Develop curated, production‑grade data models (star/snowflake) and semantic layers to support KPI tracking and decision support; ensure data integrity and consistency. - Partnership within Digital Technology:
Collaborate with central product and enterprise data teams to understand application architectures and source data structures; co‑develop and validate business‑ready data models for analytics, resolve data issues at the source, and align to enterprise data standards and governance. - Shop‑Floor Process Understanding:
Build deep understanding of component repair workflows, routings, and constraints; identify improvement opportunities and enable tracking of SQDIP metrics (Safety, Quality, Delivery, Inventory, Productivity). - Partner with Operations:
Collaborate with cell leaders, planners, quality, engineering, and finance to translate business questions into data products; facilitate adoption through training and feedback loops. - Data Quality Assurance:
Implement validation, anomaly detection, lineage, and monitoring to ensure high‑quality, trusted data; triage data issues and drive corrective actions with source‑system owners. - Performance and Scalability:
Optimize data transformations, queries, and storage for low‑latency analytics at scale; tune cost/performance on cloud and warehouse platforms. - Analytics and Visualization:
Build intuitive Spotfire dashboards and analytics apps that support tiered daily management, constraint management, and root‑cause analysis; deliver clear narratives with context and citations. - Reliability and Run:
Own production operations for data products—SLAs, incident response, change management, and versioning—to ensure availability and continuous improvement. - Documentation and Standards:
Maintain documentation for pipelines, models, and dashboards; uphold coding standards, CI/CD, testing, and reusability patterns. - Continuous Improvement:
Identify automation opportunities and streamline workflows; contribute to reusable analytics assets and templates to scale across sites. - Compliance and Security:
Ensure alignment with data governance, privacy, cybersecurity, and regulatory requirements; adhere to least‑privilege access and auditability.
- Bachelor’s degree in Computer Science, Data/Analytics, Engineering, Mathematics, or related STEM field from an accredited institution.
- Minimum 5 years of experience in data engineering/analytics (2+ years for exceptional candidates), with measurable business impact.
- Advanced SQL and Python; strong experience with data visualization (Spotfire preferred).
- Experience with cloud platforms (AWS or Azure) and modern data warehouses (Snowflake, Redshift, or similar).
- Strong knowledge of data modelling, ETL/ELT, and database design.
- Understanding of data governance, security, and compliance best practices.
- Excellent problem‑solving, communication, and stakeholder management skills.
- Legal authorization to work in the U.S.
- Experience in aerospace, industrial…
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