Data Engineer

Howmet Aerospace • Whitehall, MI

2d

About The Position

Howmet Aerospace seeks an experienced, driven, self-starter to fill the Data Engineer role. The position designs, develops, and supports scalable data platforms, pipelines, models, and integrations for enterprise analytics and AI initiatives across cloud and hybrid environments. The role collaborates closely with data scientists, analysts, IT teams, and business stakeholders to meet the needs of a large manufacturing enterprise. It requires effective communication and the ability to manage medium-sized projects independently or as part of, or leading, a small team.

Requirements

• Bachelor’s degree in computer science, Information Systems, Data Analytics, Engineering, or a related technical field.
• At least 3 years of experience designing and developing enterprise data, analytics, or BI solutions.
• Experience designing and developing data integration, ETL/ELT, and data warehousing using Python and PySpark.
• 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.
• Strong analytical, problem-solving, and communication skills, with the ability to collaborate effectively with business and technical teams.
• Ability to work as a self-starter, manage medium-sized projects, and work independently or participate in or lead a small team.

Nice To Haves

• Advanced SQL skills for building complex, well-tuned queries to join and shape diverse datasets.
• Experience using DevOps with Git and CI/CD.
• Experience with Power BI, DAX, Power Query, and semantic models.
• Experience using the Azure GCC High environment for data ingestion, collection, and analysis.
• Experience with Azure ML Studio, Azure Foundry, or AI-enabled tools.
• Azure certification DP-600 (Fabric Analytics Engineer Associate) or DP-700 (Fabric Data Engineer Associate).

Responsibilities

• Collaborate with data scientists, data analysts, IT counterparts, and business stakeholders to define reporting requirements, KPIs, and analytics solutions.
• Design, develop, and support scalable data lake, lakehouse, data warehouse, and AI-enabled data platforms across cloud and hybrid environments.
• Model, build, and optimize complex, scalable ETL/ELT pipelines using SQL, Python, PySpark, Azure Data Factory, Microsoft Fabric, or similar technologies.
• Design scalable data models and integration patterns for 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, and enterprise applications.
• Implement data validation, monitoring, quality controls, governance practices, and processes that support optimal pipeline and model performance.
• Develop reusable semantic models, datasets, and data products that enable self-service analytics.
• Support business analysts with data model and query design and tuning for tools such as Power BI and Python scripts.
• Optimize Power BI performance, data refresh processes, and security, including Row-Level Security and workspace governance.
• Optimize SQL queries and data processing performance to deliver scalable and efficient data solutions.
• Evaluate emerging data and AI technologies and recommend solutions to improve business processes and operational efficiency.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level