Senior Data Engineer — Cloud ETL & AWS Data Architecture

Blend360; Bogotá ciudad; Hybrid; COP 133,920,000 - 200,880,000; Full time

Benefits offered by this job

AWS/Databricks/Snowflake certs

Udemy Business access

English lessons

Job summary

Blend360 is seeking a Lead Data Engineer to design, build, and maintain enterprise data solutions. You will own the middle layer of the data pipeline, integrate diverse data sources, and optimize high-volume workloads for reliable dashboards.

You will collaborate with engineers and data product owners, manage AWS resources, and design data structures that minimize compute while supporting analytics across Tableau-ready datasets. Strong SQL, Spark, and ETL expertise required.

Qualifications

• 5+ years in Data Engineering or Data Architecture.
• Strong AWS experience for data processing.
• Proficiency in SQL and Spark.
• Experience building ETL pipelines and data integration.
• Independent problem-solving and collaboration with teams.
• Advanced English (B2+).

Responsibilities

• Own the middle layer of the data pipeline and integrate multiple data sources.
• Build and maintain ETL workflows with daily, weekly, monthly schedules.
• Develop and manage AWS processing resources and prepare datasets for analytics.
• Design data structures for efficient dashboard performance.
• Troubleshoot data discrepancies and adapt workflows as needed.
• Collaborate with engineers, developers, and data product owners.

Skills

+5 years in Data Engineering or Data /

AWS experience

SQL

Spark

ETL pipelines

Data integration

English (B2+)

Tools

AWS

Spark

Databricks

Snowflake

Job description

Blend360 is seeking a Lead Data Engineer to design, build, and maintain enterprise data solutions. You will own the middle layer of the data pipeline, integrate diverse data sources, and optimize high-volume workloads for reliable dashboards.

You will collaborate with engineers and data product owners, manage AWS resources, and design data structures that minimize compute while supporting analytics across Tableau-ready datasets. Strong SQL, Spark, and ETL expertise required.