Data Engineer

1 day ago

Singapore ADACTIN GROUP PTE. LTD. Full time

Roles & Responsibilities The Senior Data Engineer plays a critical role in designing, developing, and maintaining scalable data infrastructure and pipelines. This position supports data-driven decision-making across the organization by ensuring data quality, accessibility, and performance . The role involves end-to-end data management — from data ingestion using enterprise tools like SAP, Oracle, and Salesforce , through data transformation and gold layer creation , to Power BI report development from the gold data layer. Roles and Responsibilities: Data Pipeline Development: Design, build, and maintain robust, scalable data pipelines using tools such as Apache Airflow, Kafka, and Spark . Data Architecture: Develop and optimize data models , data warehouses , and ETL/ELT processes to support analytics and machine learning initiatives. Collaboration: Work closely with data scientists, analysts, and software engineers to understand requirements and deliver data solutions. Data Quality & Governance: Ensure data integrity through validation checks and implement data governance and security policies . Performance Optimization: Monitor and enhance data processing speed , system uptime , and query performance . Leadership & Mentorship: Guide junior engineers , promote best practices , and foster a culture of continuous learning . Innovation & Research: Stay current with emerging technologies in AI, automation, and data streaming , and lead their integration into existing systems. Other duties as required. Requirements: Education & Experience: Bachelor’s or Master’s degree in Computer Science, Data Science, Information Technology , or a related field. 6+ years of hands-on experience in data engineering or a related discipline. Technical Skills (Mandatory): End-to-End Data Workflow: Experience with data ingestion from SAP, Oracle, Salesforce , followed by data transformation , Gold Layer build , and Power BI reporting. Programming Languages: Proficiency in SQL and Python . ETL/ELT Tools: Strong experience in building and maintaining ETL pipelines . Microsoft Azure & Data Fabric Expertise: Azure Data Factory Microsoft Fabric Azure Synapse Analytics Azure Databricks Power BI Azure SQL Database / SQL Server Azure Purview Additional Technical Knowledge: Big Data technologies (e.g., Hadoop, Spark ) Cloud platforms (Azure, AWS, GCP ) Strong understanding of data modelling , data warehousing , and stream processing Familiarity with data security , compliance , and governance frameworks (e.g., GDPR, HIPAA ) Experience with CI/CD pipelines using Azure DevOps Tell employers what skills you have Microsoft AzureOraclePipelinesInformation TechnologyMentorshipSQL ServerPythonData SciencePower BIData Warehousing

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