Job Description:
- Design, develop, and maintain scalable data pipelines and architectures to support analytics and business intelligence initiatives.
- Integrate data from multiple sources, ensuring consistency, reliability, and data quality.
- Collaborate with data analysts, scientists, and other stakeholders to define data requirements and optimize data workflows.
- Implement ETL (Extract, Transform, Load) processes for structured and unstructured data.
- Monitor and troubleshoot data systems to ensure performance, security, and efficiency.
- Document data processes, system configurations, and best practices.
- Requirements:
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field.
- Proven experience with SQL, Python, and data pipeline frameworks.
- Strong understanding of data warehousing concepts and cloud platforms (e.g., AWS, Azure, or Google Cloud).
- Experience with big data technologies such as Spark, Hadoop, or Kafka is an advantage.
- Excellent problem-solving, analytical, and communication skills.
- Ability to work both independently and collaboratively in a fast-paced environment.
- Benefits:
- Competitive salary and performance-based incentives.
- Opportunities for professional development and technical training.
- Innovative and collaborative work culture.
- Flexible or hybrid working arrangements.
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Data Engineer
N+D OPUS
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