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3 days ago
As a seasoned data engineer, you will be responsible for designing, developing and maintaining large-scale data processing systems. This role requires strong technical expertise and the ability to work effectively in a collaborative environment.
The ideal candidate will have experience with Databricks, AWS, GCP, and Azure, as well as proficiency in SQL and programming languages such as Python, Java, or Scala.
Key Responsibilities- Data Engineering: Design and develop scalable and robust data pipelines that collect, process, and store large volumes of structured and unstructured data.
- Architecture: Architect and implement data warehouses, data lakes, and other storage solutions that support analytics and reporting needs.
- Optimization: Optimize data architectures and workflows for performance, scalability, and cost-efficiency.
- Collaboration: Collaborate with data scientists and analysts to understand data requirements and ensure that data systems meet their needs.
- Documentation: Develop and maintain documentation for data systems, including data models, flow diagrams, and operational procedures.
- Education: Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field.
- Experience: 5+ years of experience in data engineering or related fields, with a focus on large-scale data systems.
- Skills: Proficiency in SQL and experience with databases such as MySQL, PostgreSQL, or NoSQL databases. Strong programming skills in languages such as Python, Java, or Scala.
- Tech Stack: Experience with ETL tools and frameworks and data pipeline orchestration. Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud platforms (AWS, GCP, Azure).
- Personal Qualities: Strong understanding of data warehousing concepts, data modeling, and schema design. Excellent problem-solving skills and attention to detail. Strong communication skills and ability to work effectively in a team-oriented environment.
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