Data Engineer Manager

TL;DR

Data Engineer Manager (Databricks/AWS): Lead, design, and scale data solutions for Journey Analytics initiatives with an accent on code quality, reusable data components, and reliable data platforms. Focus on setting technical direction, evolving data architectures, and delivering high-quality, performant datasets through automated pipelines and strong data governance.

Location: Bogotá, Colombia

Company

hirify.global is an AI services provider focused on combining data science, AI, technology, and people to deliver client impact.

What you will do

• Lead and mentor a team of data engineers, driving best practices in coding, architecture, and data engineering standards.
• Define and execute the technical strategy for Journey Analytics data platforms, ensuring scalability, maintainability, and performance.
• Oversee refactoring of legacy codebases and implement modular, reusable data components to reduce duplication across journeys.
• Manage automated data pipelines in Databricks and ensure reliable downstream consumption.
• Establish standards for scalable data modeling and ensure data quality, governance, performance, and reliability across pipelines and datasets.
• Partner with analytics, product, and engineering stakeholders to align data solutions with business priorities and mitigate risks and bottlenecks.

Requirements

• 7+ years of experience in Data Engineering.
• Strong hands-on experience with Databricks data pipelines.
• Strong experience with GitHub repositories and version control workflows.
• Proven experience refactoring and maintaining legacy codebases.
• Strong understanding of data modeling and reusable component design for analytics and reporting.
• Ability to lead independently and drive initiatives with minimal supervision after high-level direction.

Nice to have

• Experience using Genie (Databricks).

Culture & Benefits

• Flexible working options to support work-life balance.
• Access to AI learning paths, Udemy Business, and role-tailored study plans and certifications.
• English lessons for professional communication.
• Travel opportunities to attend industry conferences and meet clients.
• Company-provided equipment and mentorship/career development plans.
• Benefits may vary by location in LATAM.

Hiring process

• Recruiter screen followed by interviews to assess technical leadership and data engineering experience.
• Discussion of fit for cross-functional collaboration and ownership expectations.