обновлено 22 дня назад
Data Engineer (AWS)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer (AWS): Building and maintaining large-scale batch and real-time data pipelines, data warehouses, data lakes, and backend APIs with an accent on data transformation, cloud platforms, and scalable integration. Focus on designing production-grade ETL/ELT workflows, consolidating data silos, and ensuring reliable, governed access to high-quality datasets.
Location: Singapore, South West, Singapore
Company
operates and modernizes mission-critical technology systems and data platforms for leading businesses.
What you will do
- Design, develop, and deploy data tables, views, and marts across data warehouses, operational data stores, data lakes, and data virtualization platforms.
- Extract, clean, normalize, transform, and consolidate data from multiple sources, including web scraping where required.
- Build, launch, and maintain reliable large-scale batch and real-time data pipelines using modern data-processing frameworks.
- Develop backend APIs and work with databases to support data-driven applications.
- Collaborate with project managers, data architects, business analysts, frontend developers, designers, and data analysts.
- Work in an Agile environment with continuous integration, delivery, pair programming, and code reviews.
Requirements
- Strong skills in SQL, Python, pandas, R, or comparable tools for data cleaning and transformation.
- Experience building ETL pipelines with technologies such as SSIS, AWS DMS, AWS Lambda, ECS, EventBridge, AWS Glue, or Spring.
- Proficiency in database design and technologies including PostgreSQL, MySQL, MongoDB, Cassandra, AWS S3, Athena, and SQLite.
- Experience with Databricks, Microsoft Data Fabric, cloud platforms such as AWS, Azure, or Google Cloud, and production-grade ETL/ELT integration.
- Knowledge of data modeling, data warehouses, data marts, data lakes, data virtualization, system design, algorithms, governance, access control, and security practices.
- Familiarity with REST APIs, web protocols, Hadoop, Spark, Kafka, RabbitMQ, web scraping tools, and both Windows and Linux environments.
Culture & Benefits
- Flexible, supportive, and hybrid-friendly workplace culture.
- Well-being programs supporting financial, mental, physical, and social health.
- Access to certifications from Microsoft, Google, and Amazon.
- Personalized career development goals, continuous feedback, coaching, and hands-on learning opportunities.
- Inclusive culture focused on belonging, empathy, continuous learning, and shared success.
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