Data Engineer Specialist Scotiatech

GSG-GESTIÓN DE SERVICIOS GLOBALES S.A.S; Bogotá ciudad; Presencial; COP 90.000.000 - 130.000.000; Jornada completa

Descripción de la vacante

GSG-GESTIÓN DE SERVICIOS GLOBALES S.A.S is seeking a Data Engineer Specialist to design, build, and maintain data pipelines on Azure Databricks for international banking. You will implement lakehouse-based solutions, ensure data quality, and support migration of legacy workloads to the target platform while working with cross-functional teams.

The role requires 3-5 years in data engineering, strong PySpark/Python skills, SQL, and experience with Unity Catalog and governance.

Formación

• Bachelor's in Computer Science or related field; Master’s preferred.
• 3–5 years of Data Engineering experience in cloud environments.
• Hands-on with Azure Databricks, Delta Lake, Spark, Unity Catalog.
• Strong SQL and data warehousing concepts.
• Experience with DevOps/DataOps practices and CI/CD.

Responsabilidades

• Build, test, and maintain data pipelines and ETL/ELT on Azure Databricks.
• Collaborate with cross-functional teams to deliver data solutions.
• Implement data models and transformations for analytics and reporting.
• Monitor and optimize pipelines for quality, performance, and cost.
• Apply governance, security, and compliance standards in Azure.

Conocimientos

Azure Databricks

PySpark

Python

SQL

Data modeling

DevOps/DataOps

Lakehouse architecture

Unity Catalog

Educación

Bachelor's degree in Computer Science or related field

Master’s degree is a plus

Cloud certifications (Azure Databricks, Azure, AWS, GCP) are a plus

Herramientas

Delta Lake

Spark

Azure Databricks

Unity Catalog

Azure

Descripción del empleo

Purpose

The Data Engineer Specialist designs, develops, and maintains data pipelines and infrastructure on Microsoft Azure and Azure Databricks to support the creation of scalable data products for International Banking. Reporting to the Senior Data Engineer, this role focuses on implementing robust, efficient, and secure lakehouse-based data solutions that enable data-driven decision-making and support business objectives across International Banking markets, while contributing to the migration and rationalization of legacy workloads onto the Azure Databricks target platform.

Accountabilities

• Build, test, and maintain data pipelines and ETL/ELT processes on Azure and Azure Databricks (Delta Lake, medallion architecture) to ensure reliable and efficient data flow for data products.
• Collaborate with the Senior Data Engineer and cross-functional teams (Data Scientists, Product Owners, Architecture, and Platform Engineering) to understand requirements and deliver high-quality data solutions aligned with international business goals.
• Implement data models, schemas, and transformations (dimensional and Data Vault patterns) to support analytics and reporting needs.
• Ensure data quality, integrity, and performance by monitoring and optimizing data pipelines, including performance tuning and cost optimization (FinOps) of Spark workloads.
• Adhere to and help apply data governance, security, and compliance standards within Azure environments, including Unity Catalog, role-based access control, data lineage, encryption, and key management.
• Troubleshoot and resolve issues in data pipelines to minimize downtime and ensure operational efficiency, performing root-cause analysis where needed.
• Contribute to the adoption of best practices and tools for data engineering, including documentation, automated testing, and DevOps/DataOps practices.
• Support the migration and rationalization of legacy workloads (including existing Google Cloud Platform estates) onto the Azure Databricks target platform, minimizing business and regulatory risk.
• Stay updated on modern Azure and Databricks data engineering trends and tools to enhance pipeline capabilities.

Reporting Relationships

Primary Manager:

Direct Reports:

Shared Reports NA

Dimensions NA

Education / Experience / Other Information (include only those that are specific to the role)

Education

• Bachelor’s degree in Computer Science, Data Engineering, Information Technology, Software Engineering, or a related field.
• A Master’s degree is considered a plus.
• Relevant cloud or data engineering certifications (Databricks, GCP, Azure, AWS) are considered a plus.

Experience

• 3-5 years of experience in Data Engineering, designing and developing scalable data solutions in cloud environments.
• Hands-on experience with Azure Databricks, including data pipeline development, Delta Lake, Spark, notebooks, workflows, Unity Catalog, and Lakehouse architecture.
• Strong proficiency in Apache Spark (PySpark) and Python for large-scale data processing.
• Experience building batch and streaming data pipelines using modern data engineering practices.
• Knowledge of data migration, cloud modernization, and platform transformation initiatives is highly desirable.
• Strong SQL skills and experience working with large-scale analytical databases and data warehouses.
• Experience with data modeling, schema design, and data warehousing concepts.
• Familiarity with DevOps and DataOps practices, including Git-based version control, CI/CD pipelines, automated testing, and deployment processes.

Working Conditions

Work in a standard office-based environment; non-standard hours are a common occurrenc