Data Engineer
Sunday ดูงานทั้งหมด
- กรุงเทพฯ
- งานประจำ
- ฟูลไทม์
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.
- Joining analytics and data science squad to build tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product Owner, Data and UI/UX teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data secure across all boundaries through multiple AWS regions.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data' data pipelines, architectures and data sets including relational, non-relational data structures, file system, stream and sensor data handling.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful project performing task in manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable data stores.
- 3+ years of experience in a Data Engineer or related role. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres, DB2, MariaDB and Cassandra.
- Experience with data pipeline and workflow management tools i.e. Airflow, etc.
- Experience with AWS cloud services: EC2, RDS,, S3 and Athena
- Experience with data lakehouse architecture: databricks, snowflake
- Experience with object-oriented/object function scripting languages: Python, Java, Scala, etc.