We are looking for a Data Engineer to help build the systems that make data reliable, accessible, and useful across the organization.

You will work across the full data lifecycle, from ingestion and transformation to storage, processing, and delivery. The role combines software engineering principles with modern cloud and data technologies, giving you the opportunity to work on systems that need to perform reliably as data volumes and business requirements grow.

You will collaborate with engineering, analytics, and product teams while taking ownership of the technical solutions behind critical data workflows.

Data Systems & Pipelines

- Design and develop production-grade data pipelines for batch and event-driven workloads.
- Build and maintain ETL/ELT processes that move and transform data across different systems.
- Improve existing workflows to increase reliability, scalability, and processing efficiency.
- Investigate pipeline failures and implement long-term solutions rather than temporary fixes.

Data Modeling & Delivery
- Design data structures that support analytics, reporting, and downstream applications.
- Transform raw and distributed data into consistent, well-organized datasets.
- Work with internal stakeholders to understand how data will be consumed and design appropriate solutions.
- Ensure datasets remain accurate, traceable, and dependable as the underlying systems evolve.

Cloud & Distributed Processing
- Develop solutions within an AWS-based environment.
- Work with large-scale processing workloads using technologies such as Apache Spark.
- Contribute to cloud infrastructure involving services such as Amazon S3, SNS, SQS, ECS/Fargate, and EMR.
- Evaluate technical approaches based on performance, reliability, scalability, and operational requirements.





Engineering Quality
- Establish and maintain automated checks to identify data quality issues.
- Contribute to unit, integration, and pipeline testing.
- Participate in CI/CD processes for data applications and infrastructure.
- Monitor production workflows and help establish effective observability practices.
- Document technical decisions, system behavior, and operational procedures.

Architecture & Continuous Improvement
- Participate in the evolution of the organization's data architecture.
- Contribute to the design of scalable data lake and lakehouse solutions.
- Identify opportunities to simplify existing systems and reduce operational complexity.
- Help evaluate new technologies and approaches that can improve the overall data ecosystem.

What We're Looking For
- Professional experience in data engineering, software engineering, or a closely related technical discipline.
- Strong understanding of data pipelines and ETL/ELT architectures.
- Hands-on experience building or maintaining production data workflows.
- Solid knowledge of data modeling and data transformation.
- Experience working with AWS cloud services.
- Practical experience with Apache Spark or another distributed data processing technology.
- Experience working with data stored in cloud-based environments, particularly Amazon S3.
- Familiarity with messaging or event-driven services such as SNS and SQS.
- Understanding of containerized or cloud-based compute environments such as ECS/Fargate or EMR.
- Experience with automated testing, CI/CD, version control, and production monitoring.
- Familiarity with data lake or lakehouse concepts.
- Strong troubleshooting and analytical skills.
- Ability to communicate technical concepts clearly and work effectively with cross-functional teams.

📌 Data Engineer | Colombia | Remote
🏢 Solvenza Solutions
📍 Colombia