Data Engineer (AWS)

TL;DR

Data Engineer: Crafting and shaping data platforms into powerful tools for decision-makers, ensuring pristine, harmonized data is available for strategic decisions and innovation, with an accent on engineering the backbone of data infrastructure and transforming raw data into actionable insights. Focus on designing and building data pipelines, uncovering quality issues, and scrutinizing data solutions for business and technical alignment.

Location: Hybrid, requiring a minimum of 2 days per week in hirify.global's Medellín office, Colombia.

Company

hirify.global designs, builds, manages, and modernizes mission-critical technology systems that the world depends on every day.

What you will do

• Craft and shape data platforms into powerful tools for decision-makers.
• Engineer the backbone of data infrastructure to ensure pristine, refined datasets are available.
• Transform raw data into actionable insights that drive strategic decisions and innovation.
• Architect data pipelines to cleanse, normalize, and transform raw data.
• Scrutinize data solutions to ensure alignment with business and technical requirements.
• Manage the data lifecycle to keep data fresh and impactful.

Requirements

• Minimum 4 years designing and building data pipelines end-to-end using tools such as Databricks, AWS Glue, or Google Dataproc.
• Experience as a Data Engineer and/or leading cloud modernization (AWS preferred; Azure/GCP accepted).
• Hands-on automation with Ansible (playbooks, roles, inventories) integrated with CI/CD for data workflows.
• Development experience in Java and Python for data engineering and automation.
• Strong ETL and data storage expertise with proficiency in PostgreSQL, DB2, and MongoDB.
• Experience with Big Data processing and building Power BI dashboards and operational reports.

Nice to have

• Data Modeling (conceptual/logical) aligned to business processes and service KPIs.
• Professional certifications (e.g., Open Certified Technical Specialist – Data Engineering).
• Cloud certifications: AWS Certified Data Analytics – Specialty, Google Cloud Professional Data Engineer, Microsoft Certified: Azure Data Engineer Associate, Elastic Certified Engineer.
• Collaboration tooling (GitHub/GitLab) and IDEs (Visual Studio); experience with CI/CD for data code and IaC.

Culture & Benefits

• Opportunities for career growth and specialization.
• Hands-on experience with state-of-the-art resources and Fortune 100 clients.
• Access to industry-leading learning programs and certifications (Microsoft, Google, Amazon, Skillsoft).
• Employee well-being benefits that support you and your family.
• Company-wide volunteering and giving platform.