Lead Data Engineer - AWS, ETL & Data Architecture

Blend; Bogotá ciudad; On-site; COP 180,000,000 - 280,000,000; Full time

Benefits offered by this job

AWS Certifications

Databricks access

Snowflake training

Udemy Business access

English lessons

Travel opportunities

Job summary

Blend is seeking a Lead Data Engineer to design, build, and maintain enterprise data solutions across data warehouses, ODS, and other data stores. You will own the middle layer of the data pipeline, integrating Quantum interaction data with operational datasets, and oversee ETL workflows on daily to monthly cadences.

The role requires strong SQL and Spark skills, hands-on AWS experience, and the ability to translate business needs into reliable data architectures.

Qualifications

• 5+ years of experience in Data Engineering, Data Architecture, or a related field.
• Hands-on AWS experience managing data processing resources.
• Proficiency in SQL and experience with Spark.
• Experience building ETL pipelines and integrating multiple data sources.
• Investigative mindset and ability to solve ambiguous technical problems.
• Collaborative with the team and own assigned work within an established group.
• Advanced English (B2+).

Responsibilities

• Own the middle layer of the data pipeline, combining Quantum interaction data with other sources.
• Build and maintain ETL workflows on daily, weekly, and monthly schedules.
• Develop and manage AWS processing resources and prepare datasets for Tableau.
• Design and maintain data structures that minimize compute and improve dashboards.
• Investigate data discrepancies and troubleshoot pipeline issues as needs evolve.
• Collaborate with the engineering lead, data engineers, developers, and data product owners as pipelines grow.

Skills

Data engineering

Analytical thinking

Team collaboration

English proficiency

Tools

AWS

SQL

Spark

ETL

Tableau

Databricks

Snowflake

Job description

Blend is seeking a Lead Data Engineer to design, build, and maintain enterprise data solutions across data warehouses, ODS, and other data stores. You will own the middle layer of the data pipeline, integrating Quantum interaction data with operational datasets, and oversee ETL workflows on daily to monthly cadences.

The role requires strong SQL and Spark skills, hands-on AWS experience, and the ability to translate business needs into reliable data architectures.