Data Engineer / Data Scientist – Machine Learning and Generative AI
Humblebee
Build machine-learning and generative AI solutions at Swedish digital service studio Humblebee, turning client challenges into scalable data products.
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UPS — ауқымды тасымалдау және жеткізу желісі арқылы кәсіпорындар мен жеке тұлғаларды байланыстыратын жаһандық логистика және сәлемдеме жеткізу компаниясы. Оның қызметкерлері сәлемдеме жеткізу, тасымалдау, денсаулық сақтау саласындағы логистика және оларға қатысты кәсіби операциялар бағыттарындағы қызметтерді қамтамасыз етеді. Компаниядағы жұмыс мүмкіндіктері АҚШ-та және басқа елдердегі нысандарда маусымдық қолдау, көлік жүргізу, қойма операциялары және корпоративтік лауазымдарды қамтиды. Сондықтан UPS логистикаға, жеткізу тізбегіне, клиенттерге қызмет көрсетуге және бизнес функцияларына қызығушылық танытатын үміткерлер үшін ауқымды жұмыс беруші болып табылады.
Senior Data Engineer at UPS - Onsite in United States
Build batch and real-time data pipelines for UPS data science and machine learning initiatives. Integrate, transform, govern, and deliver enterprise data for analytics and business decisions.
Сипаттама
- Lead and support data engineering initiatives, applying software and application development expertise to build solutions.
- Create and maintain clear documentation for data engineering work.
- Gather requirements, establish project scope, and integrate data across engineering initiatives.
- Evaluate analytical reporting products and tools while supporting adoption of emerging technologies.
- Maintain and support data engineering systems and processes.
- Develop implementation strategies and deliver backup, recovery, and technology solutions for proof-of-concept analysis.
- Extract, transform, and load data from multiple sources into databases or business intelligence platforms.
- Develop data APIs that enable data scientists and business intelligence analysts to query information.
- Write code in Python, Java, Scala, C++, or other languages used for statistical analysis and modeling.
- Create batch and real-time pipelines that support data science and machine learning.
- Connect internal and external data sources for engineering and analytical use.
- Perform ETL conversions, data cleansing, and data enrichment.
- Oversee the complete systems life cycle from analysis and technical requirements through design, coding, testing, and implementation.
- Combine disparate sources into reusable, reproducible data assets.
- Support data science by tuning features for analytical models.
- Mentor team members and communicate data analyses and findings to stakeholders.
Талаптар
- Command of programming languages used for statistical modeling and analysis, data warehousing, cloud solutions, and data pipeline development.
- Strong knowledge of database systems and data warehousing platforms.
- Strong understanding of how data connects operational and business functions.
- Strong knowledge of the data life cycle, including collection, transformation, analysis, secure storage, and access.
- Strong understanding of scalable data environments, including throughput, large-scale analysis, real-time prediction, security, regulation, and compliance.
- Strong knowledge of algorithms, data structures, filtering, and optimization.
- Strong understanding of analytical reporting technologies and environments such as PBI.
- Strong knowledge of at least one cloud platform, such as GCP, Azure, or AWS.
- Proficiency with Databricks notebooks and Python, SQL, and PySpark for data transformation, modeling, and analysis.
- Strong communication and storytelling abilities, including explaining complex data concepts in clear, non-technical language.
- Experience collaborating with cross-functional teams in product, operations, finance, marketing, and compliance.
- Understanding of business KPIs, metrics, and domain-specific data models.
- Experience gathering requirements and managing stakeholders.
- Knowledge of Unity Catalog for governance, lineage, permissions, and secure data sharing.
- Understanding of data versioning, ACID transactions, and Delta Lake time travel.
- Understanding of machine learning algorithms.
- Understanding of distributed systems and the business problem they support.
- Bachelor’s degree in MIS, mathematics, statistics, or computer science, an international equivalent, or equivalent professional experience.
- Currently located in the job’s geographic area or willing to relocate independently.
- U.S. citizen or national, lawful permanent resident, or an individual authorized to work in the U.S. for this employer.
Артықшылықтар
- Permanent, full-time employment.
- Equal opportunity workplace committed to preventing discrimination, harassment, and retaliation.
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