Requirements

Expected technologies

Databricks

PySpark

Python

AWS

Microsoft Azure

Google Cloud Platform

Optional technologies

SQL

Kafka

Terraform

Apache Spark

Snowflake Data Cloud

Our requirements

• You have hands-on experience in data engineering and are comfortable working independently on moderately complex tasks.
• You’ve worked with Databricks and PySpark in real-world projects.
• You’re proficient in Python for data transformation and automation.
• You’ve used at least one cloud platform (AWS, Azure, or GCP) in a production environment.
• You communicate clearly and confidently in English.

Optional

• Solid SQL skills and understanding of data modeling.
• Exposure to CI/CD pipelines, Terraform, or other DevOps tools.
• Familiarity with streaming technologies (e.g., Kafka, Spark Streaming).
• Knowledge of cloud data storage solutions (e.g., Data Lake, Snowflake, Synapse).
• Relevant certifications (e.g., Databricks Certified Data Engineer Associate).

Your responsibilities

• Develop and maintain data processing pipelines using Databricks and PySpark.
• Collaborate with senior engineers and architects to implement scalable data solutions.
• Work with cloud-native tools to ingest, transform, and store large datasets.
• Ensure data quality, consistency, and security in cloud environments.
• Participate in code reviews and contribute to continuous improvement initiatives.