Deskripsi Pekerjaan
AME Group is seeking a highly skilled and motivated Data Engineer to join our expanding team in Jakarta Selatan. As a key member of our data infrastructure department, you will play a critical role in designing, implementing, and maintaining robust data pipelines that serve as the backbone for our research and software products.
In this position, you will work closely with data scientists, product managers, and software developers to ensure the seamless flow, quality, and availability of data. We are looking for someone who is passionate about building scalable data architectures, optimizing complex database systems, and driving data-informed decisions across the organization. If you thrive in a collaborative environment and are eager to tackle challenging data engineering problems, we want to hear from you.
Tanggung Jawab
- Design, build, and maintain scalable data pipelines to ingest, process, and store large datasets from various sources.
- Collaborate with cross-functional teams to understand data requirements and translate them into efficient technical solutions.
- Optimize and improve existing data warehouse architecture for performance, reliability, and cost-effectiveness.
- Implement data quality frameworks to ensure accuracy, consistency, and integrity across all production data systems.
- Automate manual data processes to increase team productivity and reduce operational overhead.
- Monitor data platform performance, troubleshoot production issues, and implement proactive maintenance strategies.
- Evaluate and integrate new technologies and tools to enhance our data infrastructure stack.
Kualifikasi
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
- Minimum 3+ years of experience in data engineering, backend development, or a similar data-focused role.
- Strong proficiency in programming languages such as Python, Scala, or Java.
- Advanced SQL skills and extensive experience working with relational (PostgreSQL, MySQL) and NoSQL databases.
- Experience with cloud-based data warehouses (e.g., AWS Redshift, Google BigQuery, or Snowflake).
- Solid understanding of distributed computing frameworks like Apache Spark or Apache Kafka.
- Familiarity with data orchestration tools such as Apache Airflow or Prefect.
- Strong analytical mindset and excellent problem-solving skills with a focus on data-driven outcomes.