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Howmet Aerospace

Engineered aerospace components and titanium parts

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in computer science, Information Systems, Data Analytics, Engineering, or a related technical field is required.
  • At least 3 years of experience designing and developing enterprise data, analytics, or business intelligence solutions is required.
  • Experience designing and developing data integration, ETL/ELT, and data warehousing solutions using Python and PySpark is required.
  • Experience with Microsoft Azure data services, Microsoft Fabric, or similar cloud data platforms, including Azure Data Factory, Synapse, or Fabric, and Azure Data Lake Storage, is required.
  • Advanced SQL skills for building complex, well-tuned queries to join and shape diverse datasets are preferred.
  • Experience using DevOps with Git and CI/CD is preferred.
  • Experience using Power BI, DAX, Power Query, and semantic models is preferred.
  • Experience using the Azure GCC High environment for data ingestion, collection, and analysis is preferred.
  • Experience with Azure ML Studio, Azure Foundry, or AI-enabled tools is preferred.
  • Azure DP-600 Fabric Analytics Engineer Associate or DP-700 Fabric Data Engineer Associate certification is preferred.
  • Strong analytical and problem-solving skills are required.
  • The candidate must be able to collaborate effectively with business and technical teams.
  • Effective communication skills are essential for extensive interaction with functional and IT resources.
  • The candidate must be capable of managing medium-sized projects independently or participating in and leading a small team.

Responsibilities

  • Collaborate with data scientists, data analysts, and IT counterparts to design data pipelines that fulfill the AI and analytical needs of a large manufacturing enterprise.
  • Model, build, and optimize complex, scalable ETLs and data pipelines to support on-premises and cloud-based data warehouses and data lakes using SQL and Azure technologies.
  • Implement processes and systems that ensure data quality and optimize pipeline and model performance over time.
  • Support business analysts with data model and query design and tuning for tools such as Power BI and Python scripts.
  • 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 and workspace governance.
  • Collaborate with business stakeholders to define reporting requirements, key performance indicators, 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.

About the Company

Howmet Aerospace

Engineered aerospace components and titanium parts

Howmet Aerospace designs and manufactures advanced engineered components for aerospace and transportation, including jet engine parts, aerospace fastening systems, titanium structural parts, and forged wheels. These parts are precision-made from specialized materials to deliver lighter, fuel-efficient, and durable performance, supported by a large patent portfolio. It differentiates itself by offering a broad, integrated set of engineered solutions across engines, airframes, and wheels with patented technologies and materials. Its goal is to help customers achieve safer, more efficient air and land transportation by delivering reliable, high-performance components that reduce weight and emissions.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Pittsburgh, PA
Founded
1888

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