Remote Data Engineer: Cloud-Native Pipelines

BairesDev; Bogotá; Remote; COP 197,167,000 - 361,473,000; Full time

Benefits offered by this job

100% remote work

Competitive compensation in USD

Home-office hardware and software

Flexible hours

Paid parental leaves & holidays

Global, multicultural environment

Job summary

BairesDev is hiring a Data Engineer to join a global, remote-first team. You will own end-to-end data solutions, designing scalable pipelines and handling real-time data flows for thousands of users.

Expect modern cloud-native tech, distributed processing, and a strong emphasis on quality and observability. You'll work with Python for ETL, Spark for processing, and Delta Lake for data reliability, while collaborating across teams to deliver impactful data products.

Qualifications

• 5+ years of total experience in Data Engineering.
• 3+ years of experience with AWS Glue or Databricks.
• 3+ years of experience with Spark.
• 2+ years of experience with Delta Lake.
• 5+ years of experience with Python for ETL and automation.
• Familiarity with monitoring, observability, and alerting in data pipelines.
• Cloud experience.
• Advanced proficiency in English.

Responsibilities

• Design and implement scalable data pipelines with AWS Glue or Databricks.
• Develop and optimize distributed processes in Apache Spark for large data volumes.
• Manage Delta Lake tables, ensuring integrity, versioning, and schema evolution.
• Write and maintain clean Python code for ETL and automation.
• Collaborate with cross-functional teams to translate business needs into data solutions.

Skills

Data engineering experience

Python for ETL and automation

Spark

Delta Lake

Cloud experience

Monitoring / observability

English proficiency

Tools

AWS Glue

Databricks

Spark

Delta Lake

Job description

BairesDev is hiring a Data Engineer to join a global, remote-first team. You will own end-to-end data solutions, designing scalable pipelines and handling real-time data flows for thousands of users.

Expect modern cloud-native tech, distributed processing, and a strong emphasis on quality and observability. You'll work with Python for ETL, Spark for processing, and Delta Lake for data reliability, while collaborating across teams to deliver impactful data products.