Senior Data Engineer (Databricks)

Unosquare, Inc.; Colombia; On-site; COP 60,000,000 - 120,000,000; Full time

Job summary

Unosquare, Inc. is seeking a Data Engineer to design, build, and maintain data pipelines that turn raw data into stable, trusted datasets used to optimize performance.

You will work closely with Physics and Analytics Engineers to deliver production-ready data solutions and ensure data quality across teams. The role requires strong Python/SQL, Spark/PySpark, and Databricks experience, with an emphasis on scalable, observable pipelines and clear communication of complex concepts to diverse

Qualifications

• Strong data fundamentals: data modeling, data quality, ETL/ELT patterns and pipeline design.
• Advanced Python and SQL expertise.
• Hands-on with Spark and PySpark for large-scale processing.
• Experience with Databricks.
• Version control with Git and collaborative workflows.
• Proven root cause analysis, troubleshooting in production data environments.
• Ability to move between detailed technical analysis and broader system context.
• Strong communication and incident response skills.
• Strong presentation skills.
• Experience with Grafana preferred.
• Experience with scientific/physics data preferred.

Responsibilities

• Design, build, maintain and optimize data pipelines that transform raw data into stable, reliable datasets used for performance optimization.
• Collaborate closely with Physics and Analytics Engineers to understand data needs and turn them into production solutions.
• Turn lab and exploratory datasets into trusted, documented, shared datasets.
• Translate scientific and analytical concepts into scalable, production-ready code.
• Gather and clarify requirements with stakeholders, and confirm that delivered data meets their needs.
• Lead or support incident response for data issues, including root cause analysis, troubleshooting and debugging across the pipeline.
• Monitor pipeline health and data quality, and build dashboards and alerts that make issues visible early.
• Present findings, designs and status updates to technical and non-technical audiences.

Skills

Python

SQL

Spark / PySpark

Databricks

Git

Root cause analysis

Communication

Presentation

Grafana

Scientific data

Tools

Grafana

Databricks

Git

Job description

We are looking for a Data Engineer to build and maintain the data pipelines that turn raw data into stable, trusted datasets used to optimize performance. Working closely with Physics and Analytics Engineers, you will take exploratory and lab-built datasets and make them production-grade and shared across teams. The role suits someone who is comfortable going deep into technical detail while keeping the wider system in view. You should be able to turn scientific concepts into reliable, production-ready code and explain your work clearly to both technical and non-technical audiences.

Key Responsibilities

• Design, build, maintain and optimize data pipelines that transform raw data into stable, reliable datasets used for performance optimization.
• Collaborate closely with Physics and Analytics Engineers to understand data needs and turn them into production solutions.
• Turn lab and exploratory datasets into trusted, documented, shared datasets.
• Translate scientific and analytical concepts into scalable, production-ready code.
• Gather and clarify requirements with stakeholders, and confirm that delivered data meets their needs.
• Lead or support incident response for data issues, including root cause analysis, troubleshooting and debugging across the pipeline.
• Monitor pipeline health and data quality, and build dashboards and alerts that make issues visible early.
• Present findings, designs and status updates to technical and non-technical audiences.

Qualifications

• Strong data fundamentals: data modeling, data quality, ETL/ELT patterns and pipeline design.
• Advanced proficiency in Python and SQL.
• Hands-on experience with Spark and PySpark for large-scale data processing.
• Experience with Databricks.
• Version control with Git, including collaborative branching and code review workflows.
• Proven root cause analysis, troubleshooting and debugging skills in production data environments.
• Ability to move between detailed technical analysis and broader system context.
• Strong communication skills, especially for requirements gathering and incident response.
• Strong presentation skills.
• Experience with Grafana for monitoring and observability (preferred).
• Background working with scientific, physics or engineering data (preferred).

Countries: Bolivia, Colombia, Mexico, Paraguay