Data Engineer

Position Summary:

As a Data Engineer in the Global Analytics Center of Excellence (CoE), your primary purpose is to design, build, and maintain scalable data pipelines and architectures. You will integrate various enterprise systems and optimize data models to support analytics and reporting. Your objective is to ensure efficient, high-quality data solutions that meet the needs of cross-functional teams, leveraging tools like MS Fabric, SQL, Python. This role is crucial for enhancing data processing workflows, ensuring data integrity, and supporting strategic business goals through effective data management. The position should be performed from a Sylvamo facility (mill or office).

Key Responsibilities:

• Data Engineering & Integration:
• What: Design, build, and maintain scalable ETL/ELT pipelines for analytics and reporting.
• How: Optimize SQL queries and Python scripts for performance and efficiency, integrate data from SAP, Oracle, and other enterprise systems, and automate data processing workflows. Implement and maintain version control using Git and GitHub, adhering to established branching and merging strategies.
• Data Modeling & Architecture:
• What: Design and implement scalable data lake and data warehouse architectures using MS Fabric.
• How: Develop and optimize star schemas and other data models for reporting and analytics, work with Data Architects and Security to ensure data integrity, governance, and scalability, and define best practices for data organization, transformation, and accessibility.
• Platform & Performance Optimization:
• What: Optimize storage and compute performance in MS Fabric and cloud environments.
• How: Ensure scalability, security, and compliance in data solutions, and implement monitoring and troubleshooting strategies for data pipelines.
• Collaboration & Best Practices:
• What: Work with Data Governance and Business Intelligence teams to ensure compliance with CoE standards.
• How: Partner with regional data teams to support cross-functional projects, and document processes, best practices, and reusable components.
  
  

Required Skills and Knowledge:

• Technical Skills
• SQL: Proficiency in writing and optimizing complex queries.
• Python: Advanced scripting for data processing and automation.
• Spark: Experience with big data processing frameworks.
• MS Fabric/Data Factory: Knowledge of data integration and pipeline creation.
• Data Modeling: Expertise in star schema and dimensional modeling.
• SAP: Familiarity with SAP data structures and integration.
• Git/GitHub: Version control and collaborative development.
• Cloud Platforms: Experience with cloud storage and compute optimization.
• Data Governance: Understanding of data security, compliance, and best practices.
• Real-time Data Processing: Knowledge of streaming architectures.
• Fluent in English
  
  

Interpersonal Skills:

• Collaboration: Ability to work effectively with cross-functional teams.
• Communication: Clear and concise communication with technical and non- technical stakeholders.
• Problem-solving: Strong analytical skills to troubleshoot and optimize data solutions.
• Strategic Thinking: Aligning data engineering efforts with enterprise goals.
• Continuous Improvement: Passion for innovation and automation.
• Documentation: Ability to document processes, best practices, and reusable components.
• Adaptability: Flexibility to work in global, cross-functional environments.
  
  

Competencies:

• Trustworthy
• Development-minded
• Inclusive and Collaborative
• Team-Oriented
• Agile
  
  

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