Data Engineer
External
Aurelius Software · SingaporePrepare for this interview
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About the role
- Develop and implement machine learning models using Python to drive business insights. - Manage large datasets on Hadoop, Snowflake, and Teradata, ensuring efficient storage and processing. - Utilize AWS (S3, Glue, Lambda, EC2, etc.) and Google Cloud (BigQuery, Cloud Storage, Dataflow, etc.) for data integration, processing, and cloud-based analytics. - Work with FSDM (Financial Services Data Model) to design and optimize financial data models for structured reporting and analysis. - Create dashboards and reports using Qlik to support data-driven decision-making. - Develop ETL workflows to ingest and transform structured and unstructured data. - Collaborate with business stakeholders to translate complex data into actionable insights. - Ensure data security, governance, and compliance across cloud and on-premise environments. Required Skills & Experience - Python - Strong proficiency in data processing, automation, and machine learning. - Hadoop, Snowflake, Teradata (FS-LDM) - Experience with big data platforms and financial data modeling. - AWS (S3, Glue, Redshift, Lambda) & Google Cloud (BigQuery, Cloud Storage, Dataflow, etc.) - Hands-on expertise in cloud-based data engineering. - Qlik - Ability to develop interactive dashboards and reports. - SQL & ETL - Strong background in data extraction, transformation, and integration. - Teradata Financial Services Data Model (FSDM) - Familiarity with its application.
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