Design, develop, and maintain scalable data pipelines and workflows

Collaborate with data scientists, analysts, and other stakeholders to ensure data availability and reliability

Implement robust data integration processes to handle diverse data sources and formats

Optimize data storage and retrieval for performance and scalability

Ensure data quality through monitoring, validation, and error handling mechanisms

Contribute to the design and implementation of data architecture to support business goals

Participate in Agile development processes to deliver high-quality solutions within defined timelines

A minimum of 3 years of experience in a Data Engineering role

Strong programming skills in Python for data processing and automation

Hands-on experience with CI/CD tools such as Terraform for deployment automation

Proficiency in AWS services for data engineering, including but not limited to S3, Lambda, Glue, and Redshift

Advanced SQL skills for querying and managing relational databases

Experience with distributed data processing frameworks such as Spark

Fluent English skills, both written and spoken, at a B2 level or higher

Experience working with Databricks or Snowflake for data processing and analytics

Familiarity with advanced data engineering tools and platforms