Howmet Aerospace
Data Engineer
Whitehall, MI and 1 more · On-site · Mid
Sites: Whitehall, MI, Wichita Falls, TX
- Discipline
- Software
- Industry
- Aerospace
Spec sheet
Automatically summarized from the employer’s posting. Check the original description below for full requirements.
Data Engineering / Analytics Program
Data Engineer at Howmet Aerospace in Whitehall, MI or Wichita Falls, TX designs and builds scalable data platforms, ETL/ELT pipelines, and data models for enterprise analytics and AI initiatives. The role requires 3+ years of experience with Azure data services, Python, PySpark, SQL, and BI tooling; collaboration with data scientists, analysts, and IT; and ability to manage medium-sized projects.
3+ years · Bachelor’s degree in computer science, Information Systems, Data Analytics, Engineering, or related
Required
- ETL/ELT pipelines
- Azure Data Factory
- Azure data services / Synapse / Fabric
- Python
- SQL
- Power BI
- data warehousing
- data lakes
Preferred
- PySpark
- DevOps with GIT / CI/CD
- DAX / Power Query / semantic models
- Azure ML / AI tools
- Azure GCC High
Employer description
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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