Senior Data Engineer

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:

BBG is building a data warehouse to consolidate more than a decade of fragmented and unstructured property and appraisal data into a structured, queryable foundation for analytics and AI/ML. The company plans to organize and improve the data through Bronze, Silver, and Gold layers.

As a Data Engineer, you will work alongside the Data Architect to implement the architecture, including the canonical model, taxonomy, schema boundaries, and transformation design. You will build ingestion and transformation pipelines, implement data models, orchestrate workflows, and establish the testing and operational practices needed to keep the warehouse reliable.

The environment is based on Microsoft Azure and includes Microsoft Fabric, OneLake, Spark notebooks, dbt, Fabric pipelines, and Azure SQL.

Key Responsibilities

• Build ingestion and transformation pipelines that move legacy data through raw, normalized, and curated layers.

• Implement the extraction and LLM-assisted normalization of unstructured legacy data using Spark notebooks, including human review where needed.

• Model raw, normalized, and curated data layers in dbt, including tests, documentation, and lineage.

• Orchestrate and schedule workflows using Microsoft Fabric pipelines, including retries, alerting, and dependency management.

• Write efficient and well-structured SQL and DDL based on the Data Architect’s schema, including constraints, indexes, partitioning, and quality gates.

• Build data-quality tests and validation processes that distinguish warnings requiring review from blocking failures.

• Establish CI/CD, version control, and environment-promotion processes for the data platform.

• Monitor and improve pipeline performance, cost, and reliability, and support day-to-day pipeline operations.

• Partner closely with the Data Architect and raise design questions when needed.

Required Skills & Experience

• 3–5 years of hands-on data engineering experience building production pipelines.

• Strong SQL and DDL skills, including experience with constraints, indexes, partitioning, and performance tuning.

• Hands-on experience using Spark notebooks and PySpark for large-scale data ingestion and transformation.

• Experience building layered transformations in dbt, including testing and documentation.

• Experience with pipeline orchestration using Microsoft Fabric pipelines, Azure Data Factory, Airflow, or a similar platform.

• Experience working within the Azure data ecosystem, including Microsoft Fabric, Azure SQL, or Databricks on Azure.

• Strong engineering fundamentals, including version control, CI/CD, testing, and data observability.

• Ability to implement an established architecture while identifying and communicating issues early.

Nice to Have Skills

• Direct experience with Microsoft Fabric, including Lakehouse, OneLake, and Fabric pipelines.

• Experience transforming unstructured or semi-structured legacy data into a governed data model.

• Familiarity with LLM-assisted data workflows for categorization, extraction, or normalization.

• Familiarity with real estate appraisal or valuation data, including comparable properties, adjustments, USPAP, or market data.

• Experience with data-quality frameworks such as Great Expectations or dbt tests.

• Familiarity with data-lineage and observability tools.

• Python experience beyond Spark for supporting tools and automation.

Soft Skills

• Ability to collaborate closely with the Data Architect and other technical stakeholders.

• Ability to identify and communicate design issues early.

• Strong attention to data quality and reliability.

• Clear technical communication and documentation.

• Ownership of production pipeline performance and operations.

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.