Senior Manager, Data Platform

About FMC: FMC is an agricultural sciences company that advances farming through innovative and sustainable crop protection solutions. From our industry-leading discovery pipeline to novel biological and precision technologies, we are passionate about the power of science to solve agriculture’s biggest challenges.
We employ approximately 6,400 employees at more than 100 sites across North America, Europe, the Middle East, Africa, Latin America, and Asia Pacific. We are looking for people to join us in creating, developing, and improving our products, processes, and markets. If you are ready to make a difference every day, FMC is ready to talk to you.

Position Overview: We seek a motivated Data Platform Manager to oversee our next-gen One FMC Data Lakehouse platform. In addition to managing a team that develops, tests, and maintains data flows across FMC applications, this role also involves supervising Data Lakehouse development and supporting data science and analytics teams. The Data Platform Manager will ensure that the architecture and team address business needs and recommend improvements in data reliability, efficiency, and quality. 

Key Responsibilities:

• Team Leadership and Management: 
  • Lead, mentor, and manage a team of data engineers, providing guidance and support to ensure project goals are met. Note: Some data engineers are offshore.
  • Handle recruitment, training, and professional development of team members. 
  • Foster a collaborative and inclusive team environment to encourage innovation and efficient problem-solving. 
• Data Architecture and System Design: 
  • Design, construct, and manage robust, scalable data architectures that support operational and analytical data needs. 
  • Oversee the development and maintenance of databases, data lakes, data warehouses, and other data systems. 
  • Ensure architectures are optimized for high availability, performance, and industry and regulatory standards compliance. 
• Data Strategy and Governance: 
  • Develop and implement data acquisition, storage, processing, and utilization strategies across the organization. 
  • Establish data governance practices to ensure data accuracy, privacy, and security. 
  • Collaborate with other departments to align data management strategies with business objectives. 
• Project Management: 
  • Plan and manage data-related projects, including setting timelines, milestones, and budgets. 
  • Ensure projects are delivered on time and within scope and budget. 
  • Coordinate with other department heads and stakeholders to ensure integration and alignment of data systems with business processes. 
• Innovation and Improvement: 
  • Stay abreast of industry trends and advancements in data technology to continually improve data systems and processes. 
  • Evaluate and implement new tools, technologies, and methodologies to enhance the data capabilities of the organization. 
  • Advocate for data-driven decision-making and promote the use of data analytics across the organization. 
• Problem Solving and Support: 
  • Troubleshoot and resolve issues in data systems and pipelines. 
  • Provide expert advice and technical support to data engineers and other teams within the organization. 
  • Ensure continuous operational excellence in data processes. 
• Communication and Collaboration: 
  • Serve as the primary liaison between the data engineering team and other business functions, ensuring clear communication and effective collaboration. 
  • Present complex data-related insights and strategies to non-technical stakeholders, including executive leadership. 

Qualifications:

• 10+ years of experience or a bachelor’s degree in a quantitative field, MS preferred  
• Experience implementing analytic platforms in at least one of the major cloud ecosystems (AWS/Azure/GCP), unlocking the potential to explore and experiment at scale.  
• Experience in implementing and developing on Databricks, as well as establishing connectors with SAP and various CRM tools.
• Demonstrated expertise in SQL, database design, data modeling, and data lakehouse development.  
• Hands-on development experience building data and analytics solutions, traditional and modern data warehouses, ETL/ELT data pipelines to process structured/semi-structured/unstructured data and drive insights  
• Working knowledge of DevOps model, automated workflows, associated CI/CD components and containers (git, Jenkins, Docker, Kubernetes, etc.)  
• Development experience in at least one or more programming languages (e.g., Java, C#, Python) and creating interoperable data exchange mechanisms (APIs, Webhooks, etc.)
• Familiarity with one or more visualization tools (Tableau, PowerBI, etc.)  
• Ability to give technical feedback on code quality, perform code reviews, suggest improvements with an eye toward readable, reliable, unit-tested code  
• Work across organizational boundaries to uncover and understand hidden business

Preferred Qualifications:

• Good understanding of data privacy, GDPR, and best practices around data encryption  
• Working knowledge of Master Data Management, Data Governance, and Data Management best practices  
• Prior experience with data management and executing batch and real-time data pipelines to tackle large-scale systems  
• Hands-on experience building on-prem, hybrid, and multi-cloud data solutions to support enterprise-wide data democratization  
• Project management experience managing vendors and system integrators to lead data engagements and drive adoption