Design and implement robust data pipelines for ingesting, processing, and storing large datasets using Hadoop, Spark, and other big data technologies.

Develop and maintain data models and schemas to ensure data quality, consistency, and accessibility for various analytical and operational needs.

Build and optimize data warehouses and data lakes to support business intelligence, reporting, and advanced analytics initiatives.

Collaborate with data scientists and analysts to understand their data requirements and provide them with the necessary data infrastructure and tools.

Implement data governance policies and procedures to ensure data security, privacy, and compliance with regulatory requirements.

Monitor and troubleshoot data pipeline performance, identify bottlenecks, and implement optimizations to improve efficiency and scalability.

Automate data integration and ETL processes to reduce manual effort and improve data accuracy.

Evaluate and recommend new data technologies and tools to enhance the data engineering capabilities of the organization.

Develop and maintain documentation for data pipelines, data models, and data governance policies.

Provide training and support to data users on how to access and utilize data resources effectively.