Mid-level Data Engineer

ROQT | Data & AI

Data Engineer developing and maintaining data pipelines using Python. Working with relational databases and various data tools in a hybrid setting.

Posted 7/4/2026full-timeMaringá • 🇧🇷 BrazilJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Proficient in developing and maintaining data pipelines using Python and advanced SQL for optimizing complex queries. Experienced with dbt for model building, Docker, and orchestrating data workflows with tools like Dagster and Airflow.

Highest-signal resume keywords

Python Data Pipeline DevelopmentAdvanced SQL OptimizationDbt Model BuildingDocker and Linux EnvironmentsData Orchestration with Dagster or Airflow

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonSQLDbtDockerLinuxData Pipeline DevelopmentData Extraction StrategiesData Ingestion ToolsClickHouseData Governance Tools

Tools & Technologies

GitDagsterAirflowDltOpenMetadata

Industry Keywords

High-Volume Relational DatabasesBI Environment MigrationsCommercial ERP Systems

Tech Stack

Tools & technologies

AirflowDockerLinuxPythonSQL

About the role

Key responsibilities & impact

Develop and maintain data pipelines in Python
Implement extraction and incremental load strategies for high-volume relational databases
Build and evolve models in dbt
Write quality tests and keep documentation up to date
Read, refactor, and optimize complex SQL queries to improve performance
Work with Docker and Linux environments
Follow a Git workflow with Pull Requests and ongoing code reviews with the team
Develop custom extractors or use ingestion tools such as dlt, orchestrate pipelines with Dagster or Airflow, and load data into analytical databases like ClickHouse.

Requirements

What you’ll need

Solid Python skills for data pipelines (2+ years)
Advanced SQL — reading, refactoring, and optimizing complex queries
dbt — hands-on experience building models, tests, and documentation
Experience with high-volume relational databases and extraction/incremental load strategies
Docker and comfort with Linux environments
Git and workflow with PRs and code review
Plus: ingestion tools like dlt or building custom extractors
Orchestrators (Dagster, Airflow)
ClickHouse or other analytical databases
Data catalog and governance tools (e.g., OpenMetadata)
Experience with BI environment migrations
Experience with commercial ERP systems

Benefits

Comp & perks

Birthday day off
Unimed health plan
Odontoprev dental plan
Mixtra
TotalPass
Life insurance
Meal allowance
Home office allowance