Big Data Engineer - Singapore - Sciente International Pte Ltd

    Sciente International Pte Ltd
    Sciente International Pte Ltd Singapore

    1 month ago

    Sciente International Pte Ltd background
    $80,000 - $120,000 per year Technology / Internet
    Description
    A great opportunity as a Data Engineer to work in cloud based data engineering, analytics and data management team in a well established company.Mandatory Skill-set
    • Bachelor's Degree in Computer Science or equivalent;
    • Minimum 5 years of experience in data engineering and data management;
    • Hands on technical experience in Azure Data Factory, Databricks, Synapse, SQL Server Integration Services;
    • Strong experience in Python / SAS / R along with Tableau / Power BI;
    • Strong experience in gathering business requirements and translating into technical specification;
    • Strong analytical skills with high curiosity to deep dive into root cause of problems and suggest solutions;
    • Has good stakeholders management experience;
    • Attention to technical details;
    • Ability to deliver tasks on time with high quality outcome;
    • Self motivated and ability to take ownership;
    • Strong written and spoken communication skills.
    Desired Skill-set
    • Azure Data Engineer Certified;
    • ITIL certified;
    • Prior experience in Python, R or Machine Learning tools
    Responsibilities
    • Design and develop data models, ETL pipelines, data integration process while ensuring data accuracy and quality;
    • Perform data analysis of structured and unstructured data and perform business intelligence initiatives such as build user friendly reports using data visualization tools;
    • Analyze ETL requirements from users and provide solutions accordingly;
    • Responsible for planning and executing data profiling and data quality analysis;
    • Monitor data pipelines, databases and analytical processes to ensure smooth operations;
    • Identify and resolve data-related issues, performance bottleneck and data quality problems;
    • Design and document data catalogs and data architectures;
    • Perform regular data cleansing exercise to ensure that data is of high quality and relevant to the business needs;
    • Execute data transformation, correction and aggregations to ensure compliance with business / regulatory requests;
    • Build and maintain reports and dashboards using suitable data visualization tools;
    • Conduct analysis on the reports and translate the findings into valuable insights to business users;
    • Prepare data for prescriptive and predictive modelling;
    • Perform database monitoring and performance tuning.

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