Description

Company Overview:

Global Technology Services is a rapidly expanding organization situated in Medellín, Colombia. We pride ourselves on possessing one of the most influential networks within software development and IT services for the entertainment, financial, and logistics sectors. Our corporate projections offer a multitude of opportunities for professionals to elevate their careers and experience substantial growth. Joining our team means engaging with expansive engineering teams across Latin America, Philippines and the United States, contributing to cutting-edge developments in multiple industries.

Currently, we are seeking a Senior Data Engineer with a strong English level to join our team. Here are the challenges that our next warrior will face and the requirements we look for:

Position Title: Senior Data Engineer

Location: LATAM

What you will be doing:

We are seeking a hands-on Data Engineer to take ownership of the day-to-day development and reliability of our data environment. You will help evolve an existing, relatively flat data structure into a more scalable and performant analytics warehouse while ensuring current pipelines and integrations remain reliable.

This role will focus primarily on data ingestion, SQL development, data modeling, normalization, and Snowflake-based analytics solutions. You will work closely with the Director of Software and Data, gradually assuming ownership of the technical data responsibilities currently managed by that role.

The ideal candidate has a genuine background in data engineering, can work independently without extensive oversight, and understands how to structure data for reliable analytical use. Over time, the position may also contribute to predictive analytics and machine-learning use cases supporting logistics and resource-planning decisions.

Key Responsibilities

• Take ownership of the day-to-day development and support of the company’s data environment.

• Build, enhance, and maintain data pipelines that ingest information from SQL Server, PostgreSQL, SaaS platforms, internal applications, APIs, and file-based sources.

• Support data replication and ingestion using tools such as Hevo, Azure Data Factory, Azure Blob Storage, and Snowflake tasks and stages.

• Continue developing the company’s Snowflake-based analytics warehouse and supporting analytical structures.

• Replace or improve existing flat data structures by designing more scalable, performant, and maintainable data models.

• Design data models that support increasingly complex analytical and operational business requirements.

• Write and optimize SQL queries, transformations, and data-processing workflows.

• Perform data acquisition, cleaning, normalization, validation, and preparation for downstream analytics.

• Monitor existing pipelines and troubleshoot data ingestion, transformation, or reliability issues when they arise.

• Integrate new data sources as business and reporting requirements evolve.

• Ensure data quality, consistency, integrity, and availability across the data environment.

• Prepare reliable datasets and analytical models for business users working within Sigma.

• Document data sources, pipelines, transformations, models, and technical processes.

• Collaborate with software engineering and business teams on products that require analytical data solutions.

• Contribute to future predictive analytics and machine-learning initiatives as the data platform matures.

• Provide after-hours support when necessary to address critical data-pipeline issues.

Required Skills & Experience

• At least 4 years of hands-on experience in data engineering, analytics engineering, or a closely related data-focused role.

• Strong SQL skills, including the ability to develop, troubleshoot, and optimize complex queries and data transformations.

• Strong understanding of data architecture, data modeling, normalization, and analytical data structures.

• Hands-on experience building and maintaining ETL/ELT pipelines.

• Experience working with Snowflake or a comparable cloud data warehouse.

• Experience integrating data from relational databases, particularly SQL Server and/or PostgreSQL.

• Experience with data-replication or integration tools such as Hevo, Fivetran, Stitch, or similar platforms.

• Experience working with Azure Data Factory or a comparable cloud-based data integration tool.

• Understanding of data ingestion patterns involving APIs, JSON files, cloud storage, stages, and scheduled processing.

• Experience with data-quality validation, monitoring, troubleshooting, and production pipeline support.

• Ability to independently take ownership of technical data responsibilities with limited day-to-day oversight.

• Demonstrated data-engineering experience rather than primarily software-development or dashboard-reporting experience.

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent professional experience.

Nice to Have Skills

• Experience with Python for data processing, automation, or analytical workloads.

• Familiarity with Python data libraries and frameworks such as Pandas, NumPy, or PySpark.

• Exposure to predictive analytics, machine learning, or demand-forecasting use cases.

• Experience with Sigma or another modern BI and analytics platform.

• Experience supporting OLAP or other analytical data structures.

• Familiarity with Azure Blob Storage.

• Experience with Snowflake tasks, stages, and file-based ingestion.

• Exposure to SQL Server Reporting Services or the migration of legacy reporting solutions.

• Experience within logistics, transportation, resource planning, or another operationally complex industry.

• Experience integrating CRM or SaaS platforms such as HubSpot.

Soft Skills

• Strong sense of ownership and accountability.

• Ability to work independently without requiring extensive supervision.

• Analytical mindset with a strong understanding of how data should be structured and used.

• Practical problem-solving and troubleshooting skills.

• Ability to understand business requirements and translate them into scalable data solutions.

• Clear communication with both technical and nontechnical stakeholders.

• Curiosity and willingness to learn unfamiliar tools and business domains.

• Attention to data accuracy, reliability, and maintainability.

• Collaborative approach when working with software developers, business users, and leadership.

Why you will love GTS:

• Join a powerful tech workforce and help us change the world through technology

• Professional development opportunities with international customers

• Collaborative work environment

• Career path and mentorship programs that will lead to new levels.

Join GTS and contribute to shaping the data landscape within a dynamic and growing organization. Your skills will be honed, and your contributions will play a vital role in our continued success. GTS is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.