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Sponsorship Visa Data Engineer jobs in Singapore

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    • Standardize and maintain data integrity to provide an efficient way in accessing data.
    • 5+ years of experience as a data engineer with a bachelor or advanced in…
    • View all SHOPLINE jobs - Singapore jobs - Data Engineer jobs in Singapore
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    • Data Analytics: Identify underlying trends and patterns in business and campaign data using statistical and computational techniques and tools; develop, apply…
    • Dataset Engineering: Develop data processing workflows for video, Physical AI, and robotics datasets, as well as synthetic data generation.
    • Implement data quality checks and validation processes to ensure data integrity and reliability.
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    • Warehouses, operational data store, data lake and data virtualization.
    • Familiar with data modelling, data access, and data storage infrastructure.
    • Implement and maintain data quality monitoring.
    • Build scalable and reusable data workflows in cloud environments (GCP, AWS, or Azure).
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    • Design, develop and deploy data tables, views and marts in data warehouses, operational data store, data lake and data virtualization.
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    • Good experience designing data solutions including data modeling.
    • Develop data transformation routines to clean, normalize, and aggregate data.
    • Design, develop, and deploy data tables, views, and marts in data warehouses, operational data stores, data lakes, and data virtualization.
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    • Design data models, schemas, data lakes and analytical datasets.
    • Demonstrated experience with data extraction, ingestion, ETL/ELT, transformation, data…
    • Design, develop and deploy data tables, views and marts in data warehouses, operational data store, data lake and data virtualization.
    • Apply statistical methods to investigate relationships within data and support data-driven decision-making.
    • Collaborate with business and technical stakeholders…
    • Strong understanding of data warehouse design (Redshift, Snowflake) and data governance principles.
    • Design and build enterprise-scale data architectures —…
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    • Integrate data from different systems and ensure data quality.
    • Design data solutions such as databases, data lakes, and data warehouses using AWS and Databricks…
    • Design, develop and deploy data tables, views and marts in data warehouses, operational data store, data lake and data virtualization.

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Job Post Details

Data Engineer - Singapore - job post

SHOPLINE
4.3 out of 5 stars
Singapore
Full-time

Job details

Job type

  • Full-time

Location

Singapore

Full job description

Data Engineer - SHOPLINE Singapore

SHOPLINE is Asia’s largest smart commerce platform. With our customers in mind, we strive to deliver scalable commerce solutions to merchants of all sizes. We’re a full-featured platform with services including online store opening, O2O solution, retail POS systems, advertising placement, business strategy consultation, marketing, and more to empower merchants to succeed in omnichannel retailing and cross-border commerce.

What you’ll be doing:

  • Responsible for collecting, designing, storing and processing payments data in the eCommerce business. In charge of unifying and standardizing data to create holistic business digital assets.

  • Play a leading role in constructing business evaluation metrics, developing tactics in data services and creating data-driven tools in alignment with Products and Operations objectives.

  • Define underlying business data requirements. Build fitted models to enhance data quality and stability. Standardize and maintain data integrity to provide an efficient way in accessing data.

Who we are looking for:

  • 5+ years of experience as a data engineer with a bachelor or advanced in Computer Science. Proven track record in data warehousing.

  • Demonstrated strength in data modeling, development and governance. Preferred experience with building ETL pipelines.

  • Expert skills in SQL and Python. Familiarity with big data technologies and solutions (Spark, Hadoop, Hive, etc.). Nice to have a background in Machine Learning.

  • Proven success in communicating across different functions and synthesizing resources to push through projects in a dynamic environment.

  • Preferred experience in tech firms, especially in the payments industry.

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