Analytics Engineer

Who Are We?

FDH Aero is a trusted global supply chain partner for aerospace and defense companies, providing end-to-end supply chain solutions for OEM and aftermarket customers.

With more than 55 years of experience and operations in 14 countries, we bring expertise across Commercial, Defense, Space, Business Aviation and Cargo through our specialized business divisions:
Electronics
, Hardware
, Commercial Aftermarket
, and Defense Aftermarket
.

For more information, please visit the FDH Aero website.

Fast-paced & Impactful Work – Every decision helps keep aircraft flying and missions moving.

Driven Team & Culture – Supportive, driven colleagues who support you every step of the way.

High-Growth Opportunities – We invest in your success with training and development.

Competitive Benefits Package – Includes medical, dental, vision insurance, Flexible Spending Accounts (FSA), 401k matching, wellness activities and more.

The Analytics Engineer is responsible for designing, building, and maintaining scalable data pipelines and models that transform raw data into trusted, analytics-ready assets for FDH Electronic’s operations. This role owns the accuracy, reliability, and performance of curated datasets across the organization and ensures business teams have access to consistent, governed insights to support critical functions. The Analytics Engineer collaborates closely with analysts and business teams to translate complex business needs into efficient data solutions while driving continuous improvement in data quality, pipeline efficiency, and self‑service analytics capabilities.

This position serves as a key technical bridge between IT and the business, enabling faster, data‑driven decision‑making in a high‑stakes global aerospace supply chain environment.

• Build scalable, modular data models to support advanced analytics, reporting, and forecasting across the aerospace supply chain.
• Transform raw data into clean, reliable, analytics‑ready tables that enable real‑time visibility into component availability, traceability, and production status.
• Develop and maintain robust SQL pipelines for curated, business‑ready datasets, incorporating incremental processing and error‑handling logic to ensure consistent data freshness and minimal downtime.
• Integrate and harmonize data to deliver accurate, unified reporting on key performance indicators.
• Define and document reusable business metrics, KPIs, and semantic models within BI tools (Power BI), ensuring consistency and governance across all self‑service reporting and dashboards.
• Enable secure, governed self‑service analytics capabilities for business, allowing them to explore performance data independently while maintaining strict data security, access controls, and compliance with aerospace industry standards.
• Implement comprehensive validation frameworks, automated testing suites, and real‑time anomaly detection mechanisms to monitor data pipelines and proactively surface potential quality issues.
• Proactively identify, investigate, and resolve data integrity problems to uphold traceability requirements and regulatory compliance.
• Improve overall pipeline efficiency, reduce processing costs, and enhance scalability to support growing data usage.
• Tune complex data models, SQL queries, and transformation logic to handle increasing data volumes and velocity driven by business growth.
• Partner closely with analysts and business teams to gather and refine requirements for data products.

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 3+ years of experience in analytics engineering, data modeling, or a similar role, preferably in supply chain, manufacturing, or aerospace industries.
• Proven track record working with large‑scale datasets in cloud and familiarity with ETL processes.
• Strong SQL skills and experience with data warehouses.
• Expertise in BI platforms and semantic modeling, with a focus on enabling user‑friendly analytics.
• Analytical mindset with excellent problem‑solving skills, capable of identifying data anomalies and optimizing performance in high‑volume…