Cloud Data Engineer - Spark, Kafka & AWS

Kunai; United States; Hybrid; USD 120,000 - 165,000; Full time

Job summary

Kunai builds data-driven banking solutions in the United States, leveraging cloud-native architectures and modern data platforms. This role focuses on engineering robust data pipelines to support critical banking initiatives and enhance data quality at scale.

You will migrate and transform large enterprise datasets, optimize both batch and streaming workflows, and collaborate with cross-functional teams to deliver reliable, scalable data services using Spark, Kafka, or Kinesis.

Qualifications

• 5+ years in Python and 4+ years in AWS.
• Strong SQL skills with PostgreSQL.
• Hands-on with Databricks, Snowflake, Airflow.
• Nice to have: Java, AWS Glue, shell scripting, and Agile experience.

Responsibilities

• Own data engineering for a critical banking initiative, using cloud-native tools.
• Migrate and transform enterprise-scale data in cloud environments.
• Optimize batch and stream processing pipelines with Spark, Kafka, or Kinesis.

Skills

Python

AWS

SQL

Tools

Databricks

Snowflake

Airflow

Kafka

Kinesis

AWS Glue

Shell scripting

Job description

Kunai builds data-driven banking solutions in the United States, leveraging cloud-native architectures and modern data platforms. This role focuses on engineering robust data pipelines to support critical banking initiatives and enhance data quality at scale.

You will migrate and transform large enterprise datasets, optimize both batch and streaming workflows, and collaborate with cross-functional teams to deliver reliable, scalable data services using Spark, Kafka, or Kinesis.