Data Engineer II: End-to-End Ingestion & Cloud Platforms

INGEPSY; Norte; Presencial; COP 280.260.000 - 373.680.000; Jornada completa

Descripción de la vacante

Kpler is seeking a Data Engineer II to own end-to-end data ingestion pipelines powering core intelligence platforms. You’ll work with Snowflake, ClickHouse, and direct client channels, building high-throughput systems from Kafka, S3, and Iceberg while ensuring reliability and observability.

Collaboration with cross-functional teams across clients and cloud infrastructure is essential. Ideal candidates bring 3+ years in data engineering, strong Java and Python skills, and a DevOps mindset

Formación

• Must-have: 3+ years professional software or data engineering experience building and operating production ingestion pipelines.
• Strong SQL, data modeling fundamentals, and experience with data warehouses (Snowflake or equivalent).
• Production cloud services ownership including monitoring, observability, and CI/CD workflows.

Responsabilidades

• Architect and maintain data ingestion pipelines from sources like Kafka, S3, and Iceberg for Snowflake/ClickHouse.
• Drive reliability with proactive monitoring, alerts, and on-call readiness.
• Lead delivery of end-to-end capabilities with peers, on schedule.
• Elevate developer experience with reusable tools and clear documentation.
• Collaborate with Cloud Platform, Product Managers, and client tech teams to align pipelines with business needs.
• Mentor engineers through code reviews and best practices.

Conocimientos

Java

Python

SQL

Kafka

S3

Airflow

Kubernetes

AWS

Data engineering

Production ownership

Herramientas

Snowflake

ClickHouse

Iceberg

Airflow

Descripción del empleo

Kpler is seeking a Data Engineer II to own end-to-end data ingestion pipelines powering core intelligence platforms. You’ll work with Snowflake, ClickHouse, and direct client channels, building high-throughput systems from Kafka, S3, and Iceberg while ensuring reliability and observability.

Collaboration with cross-functional teams across clients and cloud infrastructure is essential. Ideal candidates bring 3+ years in data engineering, strong Java and Python skills, and a DevOps mindset