Data Engineer

Responsibilities:

• Develop, maintain, and optimize ETL pipelines using Python and SQL.

• Process large datasets using PySpark or Spark.

• Work with Databricks for data engineering tasks.

• Utilize at least one public cloud platform (AWS, Azure, GCP) for data solutions.

• Collaborate with teams to design and implement data models.

• Ensure data quality, monitor pipelines, and troubleshoot issues.

Requirements:

• 2 years of experience as a Data Engineer or in a similar role.

• Proficient in Python and SQL.

• Experience with PySpark or Spark.

• Experience with Databricks.

• Experience with at least one public cloud provider (AWS, Azure, or GCP).

• Understanding of ETL, data modeling, and data warehousing concepts.

• Ability to work independently and in a team environment.