{"id":3762746,"url":"https://alion.io/job/howmet-aerospace-data-engineer","title":"Data Engineer","company":{"id":2065140,"name":"Howmet Aerospace","domain":"howmet.com","url":"https://alion.io/company/howmet","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":83,"open_postings":50,"ghost_share":0,"stale_share":0.7,"repost_share":0,"time_to_fill_p50_days":43,"computed_at":"2026-11-06T05:58:05Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Whitehall, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Power BI","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"CI/CD","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-04T14:14:54Z","employer_posted_date":"2026-11-04","last_verified_at":"2026-11-07T00:03:21Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"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:\nCollaborating 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. \nModeling, 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. \nImplementing processes and systems to ensure data quality and optimal pipeline and model performance over time. \nProviding business analysts with support for data model and query design/tuning for tools such as Power BI and Python scripts. \nExtensive 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.\nPrimary Responsibilities\nDesign, develop, and support scalable Data Lake, Lakehouse, Data Warehouse, and AI-enabled data platforms across cloud and hybrid environments.\nDesign and develop ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, or similar technologies.\nDesign scalable data models and integration patterns to support enterprise analytics and AI initiatives.\nEstablish event-driven, streaming, batch, and API-based integration patterns across enterprise systems.\nBuild and maintain data integration pipelines for plant, business unit, or enterprise applications.\nImplement data validation, monitoring, quality controls, and data governance best practices.\nDevelop reusable semantic models, datasets, and data products that enable self-service analytics.\nOptimize Power BI performance, data refresh processes, and security, including Row-Level Security (RLS) and workspace governance.\nCollaborate with business stakeholders to define reporting requirements, KPIs, and analytics solutions.\nOptimize SQL queries and data processing performance to ensure scalable and efficient data solutions. \nEvaluate emerging data and AI technologies and recommend solutions that improve business processes and operational efficiency. \n Basic Qualifications\nBachelor’s degree in computer science, Information Systems, Data Analytics, Engineering, or a related technical field.\n3+ years of experience designing and developing enterprise data, analytics, or BI solutions.\nExperience in design and development of data integration, ETL/ELT, and data warehousing using Python and PySpark \nExperience with Microsoft Azure data services, Microsoft Fabric, or similar cloud data platforms Azure Data Factory/Synapse/Fabric Azure Data Lake Storage (ADLS) \nStrong analytical, problem-solving, and communication skills, with the ability to collaborate effectively with business and technical teams. \nPreferred Qualifications\nDemonstrated use of advanced SQL skills to build complex well-tuned queries to join and shape diverse datasets. \nDemonstrated experience using DevOps with GIT and CI/CD \nDemonstrated experience using Power BI as well as DAX, Power Query, and Semantic models \nExperience using the Azure GCC High environment for data ingestion, collection and analysis \nExperience in Azure ML studio, Azure Foundry or AI enabled tools \nAccomplishment of Azure Certifications DP-600 (Fabric Analytics Engineer Associate) or (DP-700 (Fabric Data Engineer 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