Data Engineer

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)

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.

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.