Location
In office (Whitehall)
Seniority
Middle · 3+ years exp
Visa
H-1B filings in 12 months: 2
Confirmed on the employer's own hiring board on Nov 5, 2026. First seen by Alion on Nov 4, 2026. Howmet Aerospace scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Howmet Aerospace is an American manufacturer of engineered metal products for aerospace, defense and commercial transportation, headquartered in Pittsburgh, Pennsylvania. Listed on the NYSE, it reported 7.4 billion dollars of revenue in 2024 from jet engine components, aerospace fastening systems, titanium structural parts and forged wheels, with plants in the US, Mexico, Europe and Asia and Howmet Fastening Systems based in Torrance, California. Hiring covers casting and press operators, cell operators, quality inspectors, manufacturing and process engineers, maintenance and tooling staff, buyers and production supervisors.
Howmet Aerospace seeks an experienced, driven, self-starter to fill the role of Data Engineer. Successful candidates will have strong capabilities and demonstrated success in the following areas:
- Collaborating closely with data scientists, data analysts, and IT counterparts to design the data pipelines required to fulfill the AI and analytical needs of a large manufacturing enterprise.
- Modeling, building and optimizing complex scalable ETLs and data pipelines to grow and support on-premise and cloud based data warehouses and data lakes using SQL and Azure technologies.
- Implementing processes and systems to ensure data quality and optimal pipeline and model performance over time.
- Providing business analysts with support for data model and query design/tuning for tools such as Power BI and Python scripts.
Extensive interaction with functional and IT resources will be required making effective communication skills essential. The qualified candidate must be a self-starter capable of managing medium sized projects working either independently or participating in and/or leading a small team.
Primary Responsibilities
- Design, develop, and support scalable Data Lake, Lakehouse, Data Warehouse, and AI-enabled data platforms across cloud and hybrid environments.
- Design and develop ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, or similar technologies.
- Design scalable data models and integration patterns to support enterprise analytics and AI initiatives.
- Establish event-driven, streaming, batch, and API-based integration patterns across enterprise systems.
- Build and maintain data integration pipelines for plant, business unit, or enterprise applications.
- Implement data validation, monitoring, quality controls, and data governance best practices.
- Develop reusable semantic models, datasets, and data products that enable self-service analytics.
- Optimize Power BI performance, data refresh processes, and security, including Row-Level Security (RLS) and workspace governance.
- Collaborate with business stakeholders to define reporting requirements, KPIs, and analytics solutions.
- Optimize SQL queries and data processing performance to ensure scalable and efficient data solutions.
- Evaluate emerging data and AI technologies and recommend solutions that improve business processes and operational efficiency.
Basic Qualifications
- Bachelor’s degree in computer science, Information Systems, Data Analytics, Engineering, or a related technical field.
- 3+ years of experience designing and developing enterprise data, analytics, or BI solutions.
- Experience in design and development of data integration, ETL/ELT, and data warehousing using Python and PySpark
- Experience with Microsoft Azure data services, Microsoft Fabric, or similar cloud data platforms Azure Data Factory/Synapse/Fabric Azure Data Lake Storage (ADLS)
- Strong analytical, problem-solving, and communication skills, with the ability to collaborate effectively with business and technical teams.
Preferred Qualifications
- Demonstrated use of advanced SQL skills to build complex well-tuned queries to join and shape diverse datasets.
- Demonstrated experience using DevOps with GIT and CI/CD
- Demonstrated experience using Power BI as well as DAX, Power Query, and Semantic models
- Experience using the Azure GCC High environment for data ingestion, collection and analysis
- Experience in Azure ML studio, Azure Foundry or AI enabled tools
- Accomplishment of Azure Certifications DP-600 (Fabric Analytics Engineer Associate) or (DP-700 (Fabric Data Engineer Associate)
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