Senior Data Engineer
LyondellBasell
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- Senior Data Engineer
- Location:
Poznań, PL, 61-569
- Req ID: 91429
- Facility: POZNAN-6731
- Department: Data Engineering
- Division: Intermediates & Derivatives and Enterpri
LyondellBasell is a leader in the global chemical industry creating solutions for everyday sustainable living. With a nearly 70-year legacy that includes a Nobel Prize in Chemistry and our proprietary MoReTec recycling technology, LYB is enabling a more sustainable future for generations to come. LYB develops high-quality and innovative products for applications ranging from sustainable transportation and food safety to clean water and quality healthcare. LYB places high priority on diversity, equity and inclusion and is Advancing Good with an emphasis on our planet, the communities where we operate and our future workforce. We're addressing the global challenges of ending plastic waste, taking climate action, and supporting a thriving society, while generating value for our customers, investors, and society.
Come Join an Inclusive Team
We are seeking an experienced Senior Data Engineer to support the delivery of enterprise data, analytics, and digital capabilities across a wide range of business functions. This role will be responsible for designing, building, and scaling data models, products, and pipelines that enable reliable reporting, advanced analytics, operational insights, and business decision-making across the enterprise. This is a highly visible role that requires deep expertise in modern data engineering, data modeling, cloud data platforms, and distributed data processing. The successful candidate will partner closely with business and technology teams to deliver scalable, reliable, and maintainable data solutions that support enterprise initiatives and data-driven decision making. This role offers opportunities to contribute across multiple business domains, including manufacturing, supply chain, commercial operations, finance, procurement, reliability, sustainability, and other enterprise functions.
A Day in the Life
- General
- • Design, develop, and maintain scalable data pipelines, data products, and data models that support enterprise reporting, analytics, and operational decision-making.
- • Partner with business stakeholders to translate business requirements into scalable and maintainable technical solutions.
- • Ensure the quality, reliability, availability, and observability of critical data assets.
- • Collaborate with data engineers, software engineers, architects, analysts, and business teams to deliver integrated solutions.
- • Design and develop reusable Python-based pipelines, orchestration components, and data processing frameworks.
- • Write and optimize SQL for analytical and operational workloads.
- • Deliver data products and transformations as production-quality code using source control, automated testing, code reviews, and CI/CD practices.
- • Maintain technical documentation, design artifacts, and development standards.
- • Drive continuous improvement initiatives that enhance data accessibility, governance, performance, and business value.
- Area of Expertise, Requirements
- • Design and deliver enterprise data solutions supporting business-critical analytics, reporting, operational processes, and digital transformation initiatives.
- • Develop and maintain scalable analytical, operational, and dimensional data models that provide trusted and actionable business information.
- • Integrate and curate data from a wide variety of enterprise systems, applications, databases, APIs, and cloud platforms.
- • Leverage modern data engineering technologies and distributed processing frameworks to build reliable, efficient, and scalable data platforms and products.
- • Partner with cross-functional teams to standardize engineering practices, improve data quality, and accelerate delivery of enterprise data capabilities.
You Bring This Value
- • BS (MS strongly preferred, and PhD preferred) in Computer Science, Software Engineering, Computer Engineering, or related technical field.
- • For a Senior Data Engineer: 4+ years professional hands-on data engineering experience with a PhD, or 6+ years' experience with an MS degree, or 8+ years' experience with a BS degree.
- • Demonstrated experience developing and delivering production-grade data products and pipelines as code, leveraging Python, SQL, source control, automated testing, code reviews, CI/CD pipelines, and DevOps methodologies.
- • Strong data engineering experience using Python and SQL, with hands-on experience in Databricks, Snowflake, Spark, and other modern data engineering platforms for data processing, orchestration, automation, and analytics.
- • Experience designing and implementing scalable data pipelines, ETL/ELT processes, distributed data processing solutions, and analytical, operational, and dimensional data models that enable enterprise analytics, reporting, and business decision-making.
- • Experience working with large structured, semi-structured, and unstructured datasets using modern data engineering technologies, including data streaming, event-driven architectures, messaging platforms, dbt, distributed processing frameworks, and cloud-native platforms.
- • Specialty skills in large-scale computing, cluster computing, and/or cloud computing.
- • Demonstrated ability to lead technical initiatives and deliver complex projects while working effectively both independently and within cross-functional teams.
- • Experience supporting enterprise data platforms, digital transformation initiatives, data products, or large-scale data modernization efforts is strongly preferred.
- Competencies
- Drive Innovation
- Technical Skills
- Grow Capabilities
- Promote Inclusion
- Motivational Fit
- Build Partnerships
- Deliver Results
- What We Of