Product Owner

LANDMARK Group
Dubai
AED 50,000 - 200,000
Job description

Roles and responsibilities

  • Responsible for the design, implementation, and optimization of data solutions as an expert Azure Data Engineer with 6-8 years of experience
  • Proficiency in programming languages like Python, SQL, or Scala for data manipulation, transformation, and analysis
  • Expertise in data modelling, data warehousing, and data integration concepts.
  • Sound knowledge of data governance practices, data quality management, and data security principles
  • Develop efficient ETL pipelines using Azure Data Factory and ensure data quality and storage via Azure Data Lake
  • Utilize your proficiency in complex stored procedures within Azure Databricks to enable advanced analytics on data volumes exceeding 50TB
  • Collaborate cross-functionally to contribute to data-driven initiatives, leveraging Azure Synapse Analytics to provide actionable insights
  • Apply your deep understanding of the retail domain to enhance data strategies and solutions for retail-specific challenges
  • Play a pivotal role in shaping our organization's data-driven journey, driving innovation through data analytics and insights
  • Optimize data storage, processing and retrieval mechanisms for performance, cost, and scalability using data storage services (such as Azure Data Lake Storage, Azure SQL Database, etc.), data processing services (such as Azure Data Bricks, Azure Synapse, etc.) and data visualization (PowerBI, Qlik, etc.) & integration services (Data API builder, logic apps, etc.)
  • Monitor and troubleshoot data platform performance, identify and resolve issues, and provide recommendations for continuous improvement
  • Collaborate with DevOps teams to automate deployment, configuration, and monitoring processes using Azure DevOps, PowerShell, or other relevant tools
  • Stay up to date with the latest trends and advancements in cloud data services and provide recommendations on adopting new technologies or features to enhance the data platform
  • Document technical designs, procedures, and guidelines for data platform engineering and operations

Knowledge, Skills & Experience

Relevant Job Experience

  • Bachelor's degree in Computer Science, Engineering, or a related field. Advanced degree preferred
  • Proven 6-8 years’ experience in designing, implementing solutions on the Azure ecosystem including expertise in Azure services such as Azure Data Factory, Azure Databricks, Azure Machine Learning, Azure Data Lake Storage, and Azure SQL Database, Azure Synapse, PowerBI etc..
  • Experience with big data technologies such as Apache Spark, Hadoop, or similar frameworks
  • Solid understanding of cloud computing concepts and experience with cloud infrastructure management and provisioning
  • Solid understanding of network security concepts and technologies (such as firewalls, VPNs, intrusion detection/prevention systems, etc.) and data security concepts and technologies (such as access controls, encryption, observability, privacy laws/regulations, etc.)
  • Experience in a Retail setup is preferred
  • Azure certifications such as Azure Data Engineer Associate or Azure Solutions Architect Expert is preferred

Desired candidate profile

A Product Owner is a key role in agile product development, responsible for defining and prioritizing the features and requirements of a product. They act as a liaison between stakeholders, including customers and development teams, to ensure that the product aligns with business goals and user needs. Here are the key skills and responsibilities associated with this position:

Vision and Strategy

  1. Product Vision: Developing and communicating a clear product vision that aligns with the organization's goals and customer needs.
  2. Strategic Planning: Collaborating with stakeholders to define product strategy and roadmap.

Requirements Gathering

  1. User Stories: Writing and refining user stories and acceptance criteria that clearly articulate product requirements.
  2. Stakeholder Engagement: Gathering input and feedback from stakeholders, including customers, marketing, and sales teams.

Prioritization

  1. Backlog Management: Maintaining and prioritizing the product backlog to ensure that the most valuable features are delivered first.
  2. Value Assessment: Evaluating the business value and impact of features to make informed prioritization decisions.

Collaboration with Development Teams

  1. Sprint Planning: Participating in sprint planning meetings to communicate priorities and clarify requirements.
  2. Daily Stand-ups: Engaging with the development team during daily stand-ups to address questions and provide guidance.

Product Development Oversight

  1. Feature Development: Collaborating with designers and developers to ensure that features are built according to specifications and meet quality standards.
  2. Continuous Feedback: Gathering feedback during and after development to refine features and improve future iterations.

Stakeholder Communication

  1. Progress Updates: Providing regular updates to stakeholders on product development progress, timelines, and changes.
  2. Demo Sessions: Leading product demonstrations to showcase new features and gather feedback.

User-Centric Focus

  1. User Research: Conducting user research and testing to understand user needs and pain points.
  2. Usability Testing: Evaluating product usability and making recommendations for enhancements based on user feedback.

Data-Driven Decision Making

  1. Analytics: Utilizing data and analytics to inform product decisions and measure success against key performance indicators (KPIs).
  2. Market Analysis: Staying informed about market trends and competitor products to identify opportunities for differentiation.

Adaptability and Problem-Solving

  1. Flexibility: Adapting to changing market conditions, user feedback, and organizational priorities.
  2. Conflict Resolution: Navigating and resolving conflicts between stakeholders and development teams regarding product direction.
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