Deskripsi Pekerjaan
Are you ready to architect the data backbone of global enterprises? Capgemini is seeking a passionate and forward-thinking Data Engineer to join our high-performing team in Kuala Lumpur City Centre. At Capgemini, we don't just process data; we turn information into actionable insights that drive business transformation for the world’s leading brands.
As a Data Engineer, you will be at the heart of our digital transformation projects, designing robust data pipelines, optimizing cloud architectures, and ensuring high-quality data governance. You will work within a collaborative, inclusive environment where your career trajectory is defined by your ambition and supported by our world-class training programs. Whether you are scaling big data solutions or refining ETL processes, your contribution will directly impact how our clients compete in a data-driven economy.
We are looking for individuals who thrive on problem-solving and are eager to embrace cutting-edge technologies. If you are ready to be empowered to shape your career while delivering impactful solutions, we invite you to apply.
Tanggung Jawab
- Design, build, and maintain scalable data pipelines and ETL processes to support complex business requirements.
- Collaborate with cross-functional teams to define data architecture and integration strategies.
- Optimize big data platforms for performance, reliability, and cost-efficiency in cloud environments (AWS, Azure, or GCP).
- Implement data validation and quality frameworks to ensure accuracy across all data products.
- Develop and maintain data warehouses and data lakes to facilitate advanced analytics and machine learning workloads.
- Ensure compliance with data security and privacy regulations while managing large-scale data sets.
- Provide technical leadership and mentorship to junior team members while promoting best practices in data engineering.
Kualifikasi
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
- 3+ years of professional experience in data engineering, data warehousing, or software development.
- Proficiency in programming languages such as Python, Scala, or Java.
- Strong hands-on experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra).
- Proven experience with big data technologies like Apache Spark, Kafka, or Hadoop.
- Experience working with cloud-native data services (AWS Redshift/Glue, Azure Synapse, or GCP BigQuery).
- Familiarity with CI/CD pipelines, Docker, Kubernetes, and infrastructure-as-code tools is highly preferred.
- Strong analytical mindset and excellent communication skills to bridge the gap between technical and non-technical stakeholders.