Data Engineer

- Develop and maintain ETL workflows for efficient data processing and integration.

- Design and implement data pipelines using Python, Databricks, and Snowflake.

- Manage and optimize ETL processes to ensure data accuracy and reliability.

- Collaborate with cross-functional teams to identify data needs and deliver effective solutions.

- Monitor and troubleshoot data pipeline performance, proactively addressing any issues.

- Document data integration processes and workflows for clear communication across teams.

- Stay updated on industry trends and emerging technologies to enhance our data solutions.

- Proficiency in Python for data engineering tasks.

- Experience with ETL/ELT processes and data integration tools, particularly Databricks or Snowflake.

- Strong analytical skills to transform and process large datasets effectively.

- Understanding of database systems and data warehousing concepts.

- Ability to work collaboratively in a team-oriented environment.

- Excellent problem-solving skills and attention to detail.

- Strong communication skills, with the ability to convey complex technical concepts.

• Degree: Bachelor
• Age: 21 - 40
• Working time: Permanent