Product Owner Data Analytics Platform

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GENERAL DESCRIPTION

The Markets Data Analytics team in Global Products & Solutions (GPS) at Julius Baer is seeking an experienced Product Owner to lead the development and maintenance of our Data and Analytics platform. As a key member of our product management and engineering teams, you will be responsible for defining and prioritizing the product backlog, designing and implementing data architectures, and collaborating with stakeholders to deliver a scalable, secure, and user-friendly platform that meets the evolving needs of GPS.

The team consists of Data scientists, Data analysts, Data Engineers and Developers applying DataOps and MLOps to build and maintain the Markets Data Analytics Platform (DAP).

KEY FEATURES AND ACCOUNTABILITIES

Business Management

• Define and prioritize the product backlog for the Data and Analytics platform, ensuring alignment with business objectives and customer needs
• Collaborate with cross-functional teams, including other agile teams and business stakeholders, to design, develop, and deploy new features and capabilities
• Drive adoption of the data platform by identifying potential use cases
• Apply Agile methodologies to manage the development process, including sprint planning, backlog grooming, and retrospectives
• Ensure that the design, implementation, and maintenance of the Data Analytics platform is on par with the state-of-the-art methodologies and technology
• Ensure that the Data Analytics team are applying Software Development and Engineering Excellence to achieve their goals
• Ensure data quality, security, and compliance by implementing data validation and access controls
• Stay up to date with emerging trends and technologies in data engineering, data science, and cloud computing, and evaluate their potential impact on the platform
• Communicate complex technical concepts and trade-offs to non-technical stakeholders, and negotiate priorities and expectations as needed

Client management (internal & external)

• Work closely with stakeholders to gather requirements and feedback, and ensure that the deliverables meet their needs and priorities
• Collaborate with data scientists to integrate and maintain machine learning models into the platform
• Collaborate with other technical leaders to define and implement best practices, standards, and roadmaps for data engineering and architecture
• Foster a culture of collaboration, innovation, and continuous improvement within the team

Regulatory responsibilities &/or risk management

• Demonstrate appropriate values and behaviours including, but not limited to standards on honesty and integrity, due care and diligence, fair dealing (treating customers fairly), management of conflicts of interest, competence and continuous development, adequate risk management, and compliance with applicable laws and regulations

SKILLS REQUIREMENTS

Personal and Social

• Excellent communication, collaboration, and interpersonal skills, with the ability to work effectively with technical and non-technical stakeholders
• Strong analytical and problem-solving skills, with the ability to break down complex problems into manageable components
• Strong team player
• Able to work independently and in a global team setup to take on initiatives with a positive attitude
• Client-centric approach for all deliverables
• Systematic, precise and diligent working style and the ability to perform under pressure 
• Personal integrity and ethical behaviour 

Professional and Technical

• 10+ years of experience as a Data Engineer or similar role, with at least 2 years of experience as a Product Owner or similar role
• Bachelor’s degree in Computer Science, Information Technology, or a related field; advanced degree or certification in data science, engineering, or a related field is a plus
• Strong background in computer science, software engineering, or a related field, with expertise in data structures, algorithms, and software design patterns
• Experience with data platform technologies, including Spark, Deltalake, NoSQL databases, and cloud-based data platforms (e.g. Databricks, Azure Fabric)
• Proficiency in one or more programming languages, such as Python or Scala
• Experience with Agile development methodologies
• Strong understanding of data architecture, data modelling, and data governance principles, with experience designing and implementing data warehouses, data lakes, and data pipelines

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