ТаиландData Engineer (DataLake) - All levels
1 мес. назад
Таиланд
data ingestiondata transformationdata lakedata pipelinesdata qualitystreamingbatch processingdata migration
Data Engineer responsible for designing and implementing data ingestion and transformation pipelines in Data Lake projects within financial services.
Обязанности
- Developing batch, CDC and/or streaming data ingestion pipelines from multiple source systems.
- Implementing Bronze, Silver and Gold data layers , including data cleansing, transformation and standardisation.
- Developing reusable data pipelines and supporting data product implementation.
- Implementing data quality, reconciliation, validation and monitoring controls.
- Supporting data migration, integration testing, UAT and production release.
- Working with the architecture team to ensure solutions follow agreed cloud, security, governance and engineering standards .
- Supporting knowledge transfer and BAU handover.
Требования
- 4+ years of experience in data engineering or related roles.
- Strong experience in Databricks, Azure, SQL, Python/PySpark, ETL/ELT, Delta Lake, data modelling, data quality and CI/CD.
- Experience in financial services especially asset management or large-scale data transformation, would be advantageous.
- Experience in workong on an end-to-end enterprise data transformation, from source ingestion through to governed data products and business reporting.
Будет плюсом
- Experience in asset management company , fintech, or other regulated industries.
Условия
- Work on engaging projects with some of the largest banks/insurance in the world, on projects that will transform the financial services industry
- Work in a collaborative, flat, and entrepreneurial consulting culture
- Access continuous learning, training, and industry certifications
- Be part of a team shaping the future of digital financial services
- Help shape the future of digital transformation across FS & Energy
- A work culture focused on innovation and creating lasting value for our clients and employees
- Ongoing learning opportunities to help you acquire new skills or deepen existing expertise in our financial services offerings
- A flat, non-hierarchical structure that will enable you to work with senior partners and directly with clients
- An agile, diverse, entrepreneurial, inclusive, meritocratic culture
- Joining means joining an organisation that is committed to an inclusive working environment where you’re encouraged to #BeYourselfAtWork . We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It’s important to us that we recruit and develop as diverse a range of talent as we can and we believe that everyone brings something different to the table – so we’d love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help.
- #LI-PW1 #LI-Hybrid
Другое
- , a Wipro company, is a global technology and management consultancy specializing in driving digital transformation in the financial services industry. With a growing client portfolio comprising of over 100 global organizations, operates at the intersection of business and technology by combining innovative thinking with unrivalled industry knowledge to deliver end-to-end data-driven solutions and fast-track digital initiatives for banking and payments, capital markets, wealth and asset management, insurance, and the energy sector. ’s cutting-edge ingenuity is brought to life through its Innovation Labs and award-winning Be Yourself At Work culture and diverse talent.
- As a Data Engineer (Intermediate/Senior) , you will work closely with Data Architects, Business Analysts, BI developers, and client technology teams to design and implement reusable data ingestion and transformation pipelines in Data Lake/Lakehouse implementation programme