Data Engineer

Basic Function

LyondellBasell has fully committed to achieving its vision as “The Chemical Company of the Future” and an industry leader in the areas of Sustainability and Customer Experience.  The Digital Enterprise that will act as the foundation for enabling this vision will be built upon three pillars: A modern and extensible technology architecture, an ERP backbone that supports new business models, and a team of talented technologists that are empowered to build innovative solutions and digital products.  

At the intersection of these pillars, the Data & Analytics Center of Excellence (DACOE) is building the data foundation and a catalog of data products, analytical applications, and enterprise services that give users across our company the tools, data, and guidance to generate insights. This role is within the Data Solutions team, the customer facing and delivery branch of the DACOE, reporting to the Senior Manager. 

We are seeking a skilled and motivated Data Engineer to join our Data Solutions team that is focused on the development, maintenance, and optimization of our data infrastructure. The team specializes in data modeling and Power BI report development to support the objectives of our business stakeholders. 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. 
• 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.

Min. Qualifications

• Bachelor's degree in computer science, Information Systems, Business Administration or a related discipline
• 5+ years hands-on experience in architecting, developing, and successfully operationalizing complex/large scale data management projects
• Experience in data warehouse and ETL design and development using SQL on RDBMS and MPP databases
• Experience in development on Cloud (PaaS) Data Solutions, Azure preferred
• At least 3-5 years' experience in Python, and ideally also in Java, SQL, or Scala
• At least 3-5 years of experience in MS PaaS data services (examples, but not limited to: Azure data factory, Azure data lake store, Azure function apps, Azure SQL/ Data Warehouse, etc.)
• At least 3-5 years of experience in developing, designing, and deploying end to end batch / real-time solutions.

Preferred Qualifications

• Experience securing Cloud based modern data platforms
• Experience with SnowFlake
• Experience building data management (metadata, lineage, tracking etc.)  and governance solutions for modern data platforms
• Experience of working with enterprise common data models in SAP HANA, Azure SQL, manufacturing historians, various IoT, subscription and public data sources.
• Experience of Reporting and Analytics tools such as Tableau, Power BI, and Alteryx
• Experience with global enterprise environment or major consulting firm is a plus.
• DP-200: Implementing an Azure Data Solution
• DP-201-Designing an Azure Data Solution
• Microsoft Certified: Azure Data Engineer Associate
   

Competencies