Jobs Description:

Responsible for designing, developing, and maintaining data infrastructure and pipelines to enable efficient data processing and analysis. The job description typically includes:

1. Designing and implementing data architectures, data models, and ETL (Extract, Transform, Load) processes to collect and process large volumes of data.
2. Collaborating with data scientists, analysts, and stakeholders to understand data requirements and ensure the availability of accurate and relevant data.
3. Developing and optimizing data pipelines using programming languages like Python, SQL, or Scala, and technologies like Apache Spark or Hadoop.
4. Building and maintaining data warehouses, data lakes, and data repositories to ensure efficient storage and retrieval of data.
5. Ensuring data quality and implementing data governance processes, including data cleansing, validation, and security measures.
6. Monitoring and optimizing data pipelines for performance, scalability, and reliability.
7. Integrating external data sources and APIs to enrich the organization's data assets.
8. Staying updated with emerging technologies and best practices in data engineering to suggest improvements and implement new techniques.