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.
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Who We Are
Thakral One is a consulting and technology services company headquartered in Singapore, with a pan-Asian presence. We focus primarily around technology-driven consulting, adoption of value-added bespoke solutions, enabling enhanced decision support through data analytics, and embracing possibilities in the cloud. We are heavily inclined towards building capabilities collaboratively with clients and believe strongly in improving grounded and practical outcomes.
This approach is possible through our partnership with leading global technology providers and internal R&D teams. Our clients come from Financial Services, Banking, Telco, Government, Healthcare, and Consumer-oriented organisations.
