Data Engineer

AgileEngine, LLC.; Brasil; Remote; BRL 260,000 - 320,000; Full time

Benefits offered by this job

Growth opportunities

Competitive compensation

Remote work

Modern projects

Collaborative culture

Well-being programs

Job summary

AgileEngine, LLC. is seeking a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation.

Design, build, and optimize pipelines using Databricks, PySpark, and SQL; implement data quality checks and production controls; and collaborate with cross-functional teams to integrate Delta Lake, BigQuery, and evolving business requirements.

Qualifications

• 5+ years of hands-on Databricks and PySpark experience.
• Advanced SQL and data-processing skills.
• Hands-on with GCP, particularly BigQuery.
• Experience with Delta Lake and lakehouse architectures.
• Upper-intermediate English level.
• Experience building reliable, scalable data solutions.

Responsibilities

• Design, build, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.
• Build and operationalize agentic workflows to automate data engineering and production processes.
• Integrate agentic capabilities with Databricks, GCP, BigQuery, and Delta Lake environments.
• Develop data pipelines and processing solutions to support new business requirements.
• Build reusable frameworks and components across data engineering use cases.
• Implement data quality checks, monitoring, and production controls.
• Optimize PySpark and SQL workloads for performance and reliability.
• Support testing, deployment, and productionalization of data solutions.
• Troubleshoot complex data and production issues and implement sustainable solutions.
• Collaborate with business, data engineering, and platform teams to identify automation opportunities.

Skills

Analytical thinking

Troubleshooting

Production-grade data solutions

Data quality checks

Automation workflows

Testing

Version control

Collaboration

Tools

Databricks

PySpark

SQL

GCP

BigQuery

Delta Lake

ETL/ELT

Job description

About the role

We are looking for a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation.

The mandatory requirements are 5+ years of experience with Databricks and GCP, advanced SQL, and experience with Delta Lake and lakehouse architectures, along with an upper-intermediate English level. Experience building AI agents is a plus.

What you will do

• Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.
• Build and operationalize agentic workflows to automate data engineering and operational processes such as data validation, issue identification, troubleshooting, and workflow execution.
• Integrate agentic capabilities with existing Databricks, GCP, BigQuery, and Delta Lake environments.
• Develop data pipelines and processing solutions to support new business requirements and datasets.
• Build reusable frameworks and components that can be leveraged across multiple data engineering and business use cases.
• Implement data quality checks, monitoring, validation, exception handling, and production controls.
• Optimize PySpark and SQL workloads for performance, reliability, and scalability.
• Support testing, deployment, productionization, and ongoing enhancement of data and agentic solutions.
• Troubleshoot complex data and production issues and implement sustainable solutions.
• Collaborate with business, data engineering, and platform teams to identify further automation opportunities.

Must haves

• 5+ years of strong hands-on experience with Databricks and PySpark.
• Advanced SQL and data-processing skills.
• Hands-on experience with GCP, particularly BigQuery.
• Experience with Delta Lake and modern data lake/lakehouse architectures.
• Strong understanding of ETL/ELT, data pipeline design, performance optimization, and data quality.
• Experience building reliable, scalable, production-grade data solutions.
• Strong analytical and troubleshooting skills.
• Understanding of software engineering practices, including testing, version control, deployment, monitoring, and production support.
• Upper-intermediate English level.

Nice to haves

• Experience developing or integrating AI/agentic workflows, AI agents, or workflow automation solutions.
• Experience applying AI to automate data engineering, validation, troubleshooting, or operational processes.
• Familiarity with orchestration and automation frameworks.
• Experience developing reusable data engineering frameworks and platform components.
• Exposure to productionizing AI-enabled solutions with appropriate validation, monitoring, and human oversight.

Perks

• Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
• Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
• Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
• Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
• Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
• Well-being & support: access local well-being programs and people-focused support tailored to your location