Data Management Engineer Cloud ETL Sr
Softtek Colombia
IT Services and IT Consulting · 10,001+ employees
10 h ago
Mid (2-5 yrs)
Full-time
Colombia
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About the role
Design, develop, and maintain scalable data infrastructure and pipelines to support enterprise data initiatives. Ensure data quality, consistency, and reliability while collaborating with cross-functional teams to deliver effective data solutions.
What they look for
Data Engineering
ETL
ELT
Data Pipelines
Data Warehousing
Data Modeling
Data Quality
Cloud Platforms
AWS
Azure
Google Cloud Platform
Big Data
Data Governance
CI/CD
Workflow Automation
Data Architecture
Requirements
Requires 4+ years of experience in data engineering with strong hands-on skills in ETL/ELT processes and data integration. Candidates must possess knowledge of cloud-based data platforms, data modeling, and modern data architecture principles.
Full description
Requirements
Required – Technical Skills
- 4+ years of experience as a Data Engineer or in a similar data-focused role.
- Strong experience designing, building, and maintaining scalable data pipelines.
- Hands-on experience with ETL/ELT processes and data integration solutions.
- Experience working with large volumes of structured and unstructured data.
- Strong knowledge of database management, data storage technologies, and data warehousing concepts.
- Experience integrating multiple data sources and ensuring data consistency and reliability.
- Knowledge of data modeling, data transformation, and data quality best practices.
- Experience optimizing data processing performance, scalability, and availability.
- Familiarity with cloud-based data platforms and modern data architectures.
- Understanding of data governance, security, and data lifecycle management principles.
Required – Soft Skills
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Ability to work effectively with cross-functional teams and stakeholders.
- Strong attention to detail and commitment to data quality.
- Proactive mindset with a focus on continuous improvement.
- Ability to manage multiple priorities in fast-paced environments.
- Strong organizational and documentation skills.
Nice to Have (Technical Skills)
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Knowledge of Big Data technologies and distributed processing frameworks.
- Experience with data orchestration and workflow automation tools.
- Familiarity with Data Lake, Lakehouse, and modern analytics architectures.
- Knowledge of CI/CD practices for data pipelines.
- Experience supporting business intelligence and advanced analytics initiatives.
Responsibilities (Activities to Perform)
- Design, develop, and maintain scalable data infrastructure to support enterprise data initiatives.
- Build and optimize data pipelines for efficient data ingestion, transformation, and processing.
- Develop and maintain ETL/ELT solutions to ensure reliable and high-quality data delivery.
- Integrate data from multiple internal and external sources.
- Manage and optimize database storage, performance, and availability.
- Ensure data quality, consistency, integrity, and accessibility across platforms.
- Monitor and troubleshoot data workflows and pipeline performance issues.
- Collaborate with business, analytics, and technology teams to understand data requirements and deliver scalable solutions.
- Support the implementation of data governance, security, and compliance standards.
- Contribute to the continuous improvement of data architecture and engineering best practices.
- Ensure the scalability, reliability, and availability of data platforms and solutions.
Required Languages
- English: Upper-Intermediate (B2)
Additional Information
Location
- Colombia, Mexico (Hybrid)
Special Conditions
- The role requires experience working with large-scale data environments and modern data integration practices.
- Candidates should be comfortable working with multiple data sources and supporting end-to-end data lifecycle processes.
- Strong focus on data quality, scalability, reliability, and operational excellence is essential for success in this position.
