Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
Scoutfield Logo

See all jobs on Scoutfield

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
Blend360

Lead Data Engineer

Blend360

. Own the middle layer of the data pipeline, combining Quantum interaction data with account, device, and other operational data sources .

Posted 10/7/2026full-timeRemote • ColombiaSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Data Engineering and Data Architecture, with a strong focus on building and maintaining ETL workflows, managing AWS resources, and ensuring data integrity for analytics. Proficient in SQL and Spark, with a collaborative mindset to adapt to evolving application features and reporting needs.

Highest-signal resume keywords
AWS Resource ManagementETL Pipeline DevelopmentSQL ProficiencySpark ExperienceData Integration

ATS Keywords

Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Data EngineeringData ArchitectureETL WorkflowsSQLSparkData ProcessingData ValidationData StructuringData AnalyticsData Troubleshooting
Soft Skills
Investigative MindsetCollaborative ApproachOwnership
Tools & Technologies
AWSTableau
Industry Keywords
Data PipelineData SourcesOperational DataDashboard PerformanceData Discrepancies

Tech Stack

Tools & technologies
AWSETLSparkSQLTableau

About the role

Key responsibilities & impact
  • Own the middle layer of the data pipeline, combining Quantum interaction data with account, device, and other operational data sources
  • Build and maintain ETL workflows on daily, weekly, and monthly schedules
  • Develop and manage AWS processing resources
  • Validate outputs and prepare reliable datasets for Tableau
  • Design and maintain application data structures that minimize compute requirements and support efficient dashboard performance
  • Investigate data discrepancies and troubleshoot pipeline issues
  • Adapt workflows as application features and reporting needs evolve
  • Collaborate with the engineering lead, data engineers, application developers, and data product owners

Requirements

What you’ll need
  • 5+ years of experience in Data Engineering, Data Architecture, or a related field
  • Strong hands-on AWS experience, including managing resources for data processing
  • Proficiency in SQL
  • Experience with Spark
  • Experience building ETL pipelines
  • Experience integrating multiple data sources
  • Experience organizing data for analytics
  • Investigative mindset and ability to independently work through ambiguous technical problems
  • Collaborative approach and ability to take ownership of assigned work within an established team
  • Advanced English (B2+)

Benefits

Comp & perks
  • Certifications in AWS, Databricks, and Snowflake
  • Access to AI learning paths
  • Study plans, courses, and additional certifications tailored to the role
  • Access to Udemy Business courses
  • English lessons
  • Travel opportunities to attend industry conferences and meet clients
  • Career development plans and mentorship programs
  • Special day rewards for birthdays, work anniversaries, and other personal milestones
  • Company-provided equipment
  • Flexible working options
  • Other benefits may vary according to location in LATAM