Data Engineer

Design, develop, and maintain ETL/ELT pipelines to process structured and unstructured data from multiple sources.

Build and manage data lakes , data warehouses , and streaming data pipelines using cloud technologies (e.g., AWS, GCP, Azure).

Collaborate with data scientists, analysts, and software engineers to ensure data availability and quality across applications.

Implement data validation , monitoring , and observability practices to ensure pipeline reliability and accuracy.

Optimize query performance and ensure data systems are secure, scalable, and cost-effective.

Work with technologies such as SQL , Python , Spark , Airflow , Kafka , and BigQuery (or other modern data stack tools).

Maintain and document data models, lineage, and architecture for transparency and future scalability.

Automate recurring data workflows and support CI/CD pipelines using version control and DevOps tools.