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.