Description
- Identify and solve complex problems using a structured and logical approach.
- Stay up to date on the latest data engineering technologies and trends.
- Work with other engineering teams to integrate data engineering solutions with other systems.
- Maintain and optimize data systems to ensure high availability and performance.
- Design and implement data pipelines to collect, transform, and load data into data warehouses and data lakes.
- Gather requirements from stakeholders and translate them into technical specifications.
- Lead a team of data engineers in the design, development, and implementation of data engineering solutions.
- Manage functional and non-functional requirements and have a deep understanding of systems engineering methodologies.
- Build and maintain positive relationships with stakeholders, and effectively communicate technical concepts to non-technical audiences.
- Manage multiple projects simultaneously in a highly organized and efficient manner.
- Think creatively and come up with new solutions to problems.
- Communicate effectively with technical and non-technical audiences, both verbally and in writing.
Requirements
- A bachelor's Degree in Computer Science, Software Engineering, Statistics, Mathematics, or related disciplines from a reputable university.
- Minimum 6 - 10 years of relevant experience.
- Cloud computing platforms: AWS/Azure/GCP.
- Programming languages: Python/Java/Scala & Unix Shell scripting.
- Data warehouse technologies: Redshift/Snowflake/Big Query.
- Data lake technologies: Hadoop, Apache Beam, Spark, and Hive.
- Orchestration: Airflow/Control-M/(Any Orchestration tool).
- Machine learning frameworks: TensorFlow, PyTorch, and scikit-learn.
Created on | 19 Nov 2024 |
Last updated on | 19 Nov 2024 |
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