Deskripsi Pekerjaan
Clarks is seeking a skilled and innovative Data Engineer to join our dynamic technology team. In this pivotal role, you will be responsible for designing, building, and maintaining robust data pipelines that power our retail analytics and business intelligence solutions. You will play a crucial part in transforming raw data into actionable insights, ensuring our stakeholders have access to accurate, timely, and high-quality information.
As a Data Engineer at Clarks, you will collaborate closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver scalable architectures. You will work in a fast-paced environment where your expertise in data architecture and engineering will directly impact the company's ability to make data-driven decisions. If you are passionate about solving complex technical challenges and are eager to contribute to a world-renowned brand, we encourage you to apply.
Tanggung Jawab
- Design and implement scalable data architectures and ETL/ELT pipelines to ingest and process large volumes of data.
- Optimize data warehouses and data lakes to ensure high performance, reliability, and speed of data retrieval.
- Collaborate with cross-functional teams to gather, define, and document detailed data requirements and specifications.
- Perform data modeling, schema design, and database management for complex datasets.
- Implement data governance policies, data quality checks, and automated testing processes.
- Monitor system performance, troubleshoot data issues, and implement solutions to improve data availability.
- Stay updated with industry best practices and emerging technologies to continuously improve our data infrastructure.
Kualifikasi
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
- Strong proficiency in SQL and programming languages such as Python or Java.
- Experience with cloud platforms (AWS, Azure, or Google Cloud Platform) and big data technologies.
- Deep understanding of data warehousing concepts (e.g., Snowflake, Redshift, Azure Synapse) and data processing frameworks (e.g., Apache Spark, Hadoop).
- Proven experience in designing and maintaining data pipelines and ETL processes.
- Excellent problem-solving skills, attention to detail, and the ability to work independently and as part of a team.
- Strong communication skills with the ability to translate technical concepts to non-technical audiences.