• Design, develop, and maintain scalable data pipelines for the efficient collection, storage, and processing of large datasets.

• Develops and design best practices around data collection and maintain orchestration of data flows, for batch, near-real time data.

• Participates in evaluation and deployment of big data tools, relevant to the development.

• Ability to identify different platforms, techniques, and methodology used in big data platforms, and demonstrate for various system in the organization.

• Optimize and tune data systems for performance and reliability.

• Develop and implement data models and schemas to support business intelligence and analytics needs.

• Monitor and troubleshoot data pipelines to ensure smooth and efficient operation.

• Stay up-to-date with the latest advancements in data engineering and incorporate them into our data infrastructure.

• Document data engineering architectures and follow best practices.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.

• 5+ years of experience as a Data Engineer or similar role.

• Strong programming skills in Python.

• Experience with UNIX system administration using command line.

• Experience with data processing frameworks such as Airflow, Airbyte, DBT, Hadoop, Spark, Hive, and Kafka, Proficiency in SQL and experience with relational databases.

• Knowledge of data modeling, ETL processes, and data warehousing solutions.

• Knowledge of Structuring data in various schemas suitable for a data lake, warehouse, or marts.

• Experience in implementing scalable, reliable, and efficient data storage solutions with PostgreSQL, MinIO.

• Experience in enhancing the performance of big data applications, including optimizing system operations.