Data Products Specialist

As a Data Products Specialist, you will design and deliver reusable data products that support both advanced analytics users and non-technical business users. You will play a key role in strengthening self-service analytics capabilities, improving data accessibility, and enabling data-driven decision-making through scalable data engineering, cloud-based solutions, and reusable data assets.

What You'll Do and How You'll Succeed

• Design and build data pipelines and ETL processes from multiple sources to ensure data is accessible for stakeholders and supports AI and advanced analytics requirements.
• Ensure high data quality and implement monitoring mechanisms to detect and resolve data discrepancies.
• Research and evaluate new technologies and tools for data integration, analytics, and visualisation, and recommend solutions that improve data capabilities.
• Design, build, and maintain data product solutions on cloud platforms such as AWS, Azure, or GCP, while ensuring efficient resource usage and alignment with security and compliance standards.
• Promote the adoption of advanced data visualisation tools and techniques to help business users and data analysts explore and communicate insights effectively.
• Develop and maintain self-service analytics capabilities that enable users across the organisation to access and analyse data independently.
• Establish and maintain a knowledge repository for reusable data assets, including datasets, data models, code libraries, and best practices, to improve collaboration and reuse across teams.
• Collaborate closely with data scientists, data architects, data analysts, software engineers, and business stakeholders to understand requirements and deliver effective data solutions.
• Monitor and optimise data pipelines, ETL jobs, and real-time data processing workflows to improve performance and minimise latency.
• Create and maintain technical documentation, guidelines, and training materials that support data engineering and data science practices.

We'd Love to Hear From You If...

Experience

• You hold a Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or a related field.
• You have 5 to 10 years of experience in data engineering or data science roles.
• You have a strong background supporting AI and ML model development, feature engineering, and model deployment, with practical experience implementing machine learning solutions.

Technical Expertise

• You have in-depth knowledge of BI tools such as Denodo, OAS, Power BI, or similar platforms for data visualisation and reporting.
• You are proficient in cloud technologies such as AWS, Azure, or GCP, with hands-on experience building cloud-based data solutions and leveraging real-time analytics capabilities.
• You bring strong expertise in data engineering concepts including data pipelines, APIs, ETL processes, and data integration frameworks.
• You are familiar with advanced data visualisation tools such as OAS, Power BI, or similar platforms.
• You have a solid understanding of data governance, data quality, and data security principles.
• You have programming capability in Python, SQL, or Java, with experience working with large datasets and distributed computing frameworks such as Spark.

Ways of Working

• You bring strong analytical and problem-solving skills, with a detail-oriented and proactive approach.
• You communicate technical concepts clearly and effectively to non-technical stakeholders.
• You are self-motivated and able to work both independently and as part of a team.