LyondellBasell (NYSE: LYB) is one of the largest plastics, chemicals and refining companies in the world. Driven by its employees around the globe, LyondellBasell produces materials and products that are key to advancing solutions to modern challenges like enhancing food safety through lightweight and flexible packaging, protecting the purity of water supplies through stronger and more versatile pipes, improving the safety, comfort and fuel efficiency of many of the cars and trucks on the road, and ensuring the safe and effective functionality in electronics and appliances. LyondellBasell sells products into more than 100 countries and is the world's largest producer of polypropylene compounds and the largest licensor of polyolefin technologies. In 2020, LyondellBasell was named to Fortune Magazine's list of the 'World's Most Admired Companies' for the third consecutive year.
LyondellBasell has embarked upon a strategic digital transformation journey, to provide value focused and scalable digital and advanced analytics solutions across LyondellBasell's enterprise. Through working closely with other Data Engineers, Data Scientists, business domain experts, and IT, the Data Engineer will have the opportunity to provide significant tangible business value through developing and deploying scalable Data Engineering capabilities on high value problems. This requires a team of innovative, energetic, productive, software development minded, and humble individuals who demonstrate LyondellBasell's core values in the application of Data Engineering pipelines and workflows on each project.
Roles & Responsibilities
- Place emphasis on delivering value through data engineering pipelines and solutions, through excellent problem solving, development, and implementation of scalable solutions
- Work collaboratively with Data Scientists and business SMEs (Process Engineers, Automation Engineers, Reliability Engineers, other business domain experts) in providing data pipelines and workflows which are critical to delivering data driven solutions on high impact problems
- Work collaboratively with IT to ensure proper architecture, security, exception handling, testing, and code development standards are adhered to
- Develop data workflows and pipelines necessary for algorithm and ML solution deployment and maintenance for chemical manufacturing domains including predictive maintenance, reliability, preventing downtime, industrial automation and optimization, demand forecasting, and improving health and safety
- Leverage deep data engineering, architecture, advanced technologies, software development expertise, and code development standards to enable the delivery of advanced analytics projects
- Develop technical platforms, frameworks, and applications, to provide data, business intelligence, and information
- Network internally and externally to build relationships that foster technology transfer and collaboration
- BS degree in Computer Science, Software Engineering, Computer Engineering, or related technical field.
- 3 years professional hands on technical experience in software development and/or developing and implementing Data Engineering workflows, pipelines, and applications. A higher degree (Master's or PhD) with less experience is also acceptable.
- Demonstrated ability to work under the direction of others and in a team
- High level of enthusiasm and a love of data, software development, and data engineering
- Strong quantitative and problem-solving skills, including strong data, technical, and mathematical knowledge and skills
- Experience in Real Time historian data, SQL, NoSQL, and/or NewSQL database technologies
- Experience working with large structured and/or unstructured data and technologies
- Experience with modern Data Engineering, ML and Data Science libraries such as Pandas, NumPy, Scikit-Learn, NLTK, Seaborn, Dplyr
- Experience in large scale computing, cluster computing, and/or cloud computing (Azure preferably)
- Experience with Linux, Unix, Git, and software development testing frameworks
- Experience in providing data engineering solutions in various Data Science domains, such as Predictive Maintenance, Forecasting, Real Time streaming analytics, Image Analysis leveraging deep learning methodologies, and optimization
- MS strongly preferred or PhD
- 3+ years professional hands on technical experience when combined with advanced education, in software development and/or developing and implementing Data Engineering workflows, pipelines, and applications, with additional experience required in the place of advanced education
- Strong programming and scripting skills in other languages, such as C#, C++, Java, Julia, or Scala
- Experience with Azure DevOps, Jupyter Notebooks, or VS Code
- Experience with stream-processing systems, Big Data querying tools, MapReduce, MongoDB, Cassandra, integration of data from multiple data sources, ETL techniques and frameworks, and/or messaging systems
- Experienced working with Data Scientists on architecting and delivering scalable, end to end advanced analytics solutions
- Knowledge of ML techniques & algorithms, such as ANNs, SVM, GBM, Decision Forests, Clustering algorithms
- Experience with GPU technology, NVIDIA data science development stacks, and CUDA programming
- Experience with C3.ai is highly favorable, but is not expected
Builds effective teamsCollaboratesCultivates innovationCustomer focusDemonstrates courageDrives resultsEnsures accountabilityInstills trust and exemplifies integrity
Must be at least 18 years of age and must be legally authorized to work in the United States (US) on a permanent basis without visa sponsorship.
LyondellBasell does not accept or retain unsolicited résumés or phone calls and/or respond to them or to any third party representing job seekers.
LyondellBasell is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, veteran status, and other protected characteristics. The US EEO is the Law poster is available here.
Nearest Major Market: Houston