Summary
AYP is seeking a goal-oriented Data Engineer to be a part of the Technology team and work closely with the Business Intelligence team to ensure data pipelines are secure and effective.
This person will play a pivotal role in operationalising the most-urgent data and analytics initiatives for AYP's digital business initiatives. You'll be given the autonomy to innovate, create and implement tools/applications/processes. Also, you'll be tasked to work with key business stakeholders, IT experts and subject matter experts to plan and deliver optimal analytics solutions.
What you'll need:
- Passion to constantly improving existing processes with new technologies.
- Willing to learn new things.
Responsibility
- Analyze and organize raw data.
- Build data systems and pipelines.
- Evaluate business needs and objectives.
- Interpret trends and patterns.
- Conduct complex data analysis and report on results.
- Prepare data for prescriptive and predictive modelling.
- Build algorithms and prototypes.
- Combine raw information from different sources.
- Explore ways to enhance data quality and reliability.
- Identify opportunities for data acquisition.
- Develop analytical tools and programs.
- Collaborate with business intelligence team and architects on several projects.
- Curious and knowledgeable about new data initiatives.
- Participate in ensuring compliance and governance during data usage.
Skills and Qualifications
- Bachelor’s Degree in Computer Science, Data Management, Statistics, Applied Mathematics, or related field with a solid foundation.
- Min 3 years' experience in Data Management disciplines, including data integration, modelling, optimisation and data quality, and/or other areas directly with relevance to data engineering responsibilities and tasks.
- Experience with analytics tools for Object-oriented/object function scripting using languages such as R, Python, Java, C++, Scala, and/or others.
- Track record in setting up, includes designing, building and managing data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management. The ability to work with both IT and business in integrating analytics output into business processes and workflows.
- Experience in working with datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using data integration technologies.
- Experience in working with and optimizing ETL processes and data integration and data preparation flows and helping to move them into production.
- Ability to work in cross-functional teams and collaborate with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative.
Experience in the following is a plus:
- Ability to work across multiple deployment environments to the cloud, multiple operating systems and through containerization techniques such as Docker, Kubernetes, and/or AWS Elastic Container Service.
- Experience in working with both open-source and commercial message queuing technologies such as Kafka, and/or Amazon Simple Queuing Service.
- Experience working with data discovery, analytics and BI software tools like Tableau.
- Experience in working with data governance/data quality and specifically in moving data pipelines into production with appropriate data quality, governance and security standards and certification.
**We regret to inform that only shortlisted candidates will be considered and contacted. Thank you.