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.Basic Function
The Senior Data Engineer is a core member of the team responsible for providing solutions to digital age data challenges through design and implementation of an ecosystem of Cloud solutions to support AI, Machine Learning and other modern data technologies. This role will be responsible for designing, developing, optimizing, standardizing data engineering pipelines along with creating robust data models for data publishing while complying with, and adding value to, the data architecture. The Data Engineer will also be responsible for guiding the existing data engineering team and developing cloud-native solutions with low time to market by leveraging DevOps methodologies. This individual will evangelize and implement the modern practices in data engineering that address scale and are essential for digital transformation through high value driven projects.Roles & Responsibilities
- Work closely with data scientists, platform engineers, data architects, and data source owners to deliver foundational data sets, enabling analytics solutions driving successful business outcomes.
- Provide leadership in designing and implementing best practices for efficient sourcing and processing large data sets from Analytics data stores.
- Build real-time, reliable, scalable, high-performing, distributed, fault tolerant systems.
- Design and develop code, scripts and data pipelines that leverage structured and unstructured data.
- Implement measures to address data privacy, security, compliance and ensure robust data governance.
- Industrializing data lakes or real-time platforms for an enterprise enabling business applications and usage at scale
- Monitor, maintain and optimize production systems. Investigate and resolve incidents reported by users. Identify opportunities to automate, consolidate and simplify platform.
- Work with Enterprise Architecture, Digital, and other IT teams to develop and maintain data integrity, integration and governance standards.
- Contribute to the selection of platforms, data management, libraries, tool chain and OSS for software development. Stay on top of evolving technology to suggest and prototype and implement improvements to the data architecture.
- Collaborate with cross-functional teams to help utilize and drive adoption of new big data tools / models.
- Guide business stakeholder and mentor members of the data and analytics teams regarding technology and best practices.
- Manage assigned activities within time, cost and technical objectives. May manage small projects with internal or external resources.
- Bachelor's degree required
- 10+ years hands-on experience in architecting, developing, and successfully operationalizing complex/large scale data management projects
- At least 5+ years of data warehouse and ETL design and development using SQL on RDBMS and MPP databases
- Experience in big data development on Hadoop or Spark frameworks using Python, Java, noSQL, TimeSeries DBs, HDFS
- Experience in development on Cloud (PaaS) Data Solutions, Azure preferred
- Degree in Computer Science, Engineering, Technical Science or related disciplines, preferred.
- Experience building data management (metadata, lineage, tracking etc.) and governance solutions for modern data platforms
- Experience securing Cloud based modern data platforms
- Experience working with LAMBDA architecture using real-time Kafka ingestion and high-volume batch loads
- Understanding of statistics and mathematical techniques to solve real business problems.
- Experience of working with models in SAP HANA, manufacturing historians, various IoT, subscription and public data sources.
- Experience of ETL tools such as SAP BusinessObjects Data Services.
- Experience of Reporting and Analytics tools such as Tableau, Power BI, and Alteryx
- Functional experience in one of more business functions.
- Experience with global enterprise environment or major consulting firm is a plus.
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.
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