Data Engineer

Howmet Aerospace•Whitehall, MI

About The Position

Howmet Aerospace seeks an experienced, self-starting Data Engineer to design, develop, and support scalable data platforms across cloud and hybrid environments. The role supports AI and analytics needs across a large manufacturing enterprise, including Data Lake, Lakehouse, Data Warehouse, and AI-enabled platforms. The Data Engineer collaborates with data scientists, analysts, business stakeholders, and IT teams, and may manage medium-sized projects independently or participate in or lead a small team. The position involves developing and optimizing ETL/ELT pipelines and data models, establishing data integration patterns, maintaining data quality and governance, and enabling self-service analytics. It also includes supporting Power BI performance and security, advising analysts on data models and query design, and evaluating data and AI technologies to improve business processes and operational efficiency. Effective communication with functional and technical teams is essential.

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 solutions using Python and PySpark.
Experience with Microsoft Azure data services, Microsoft Fabric, or similar cloud data platforms.
Experience with Azure Data Factory, Synapse, or Fabric.
Experience with Azure Data Lake Storage (ADLS).
Strong analytical and problem-solving skills.
Strong communication skills and the ability to collaborate effectively with business and technical teams.
Ability to work as a self-starter and manage medium-sized projects independently or as part of 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 using Power BI, DAX, Power Query, and semantic models.
Experience with 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 data pipelines, 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.
Build, model, and optimize ETL/ELT pipelines using 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 for ongoing pipeline and model performance.
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.
Support business analysts with data model and query design and tuning for tools such as Power BI and Python scripts.
Optimize SQL queries and data processing to deliver scalable, efficient data solutions.
Evaluate emerging data and AI technologies and recommend solutions that improve business processes and operational efficiency.
Manage medium-sized projects independently or participate in and/or lead a small team.