Engenheiro Dados

Lever, Inc.; Brasil; Teletrabalho; BRL 180 000 - 280 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Remote work

Meal allowance

Medical insurance

Dental insurance

Online learning platform

Mentoring opportunities

Course discounts

Resumo da oferta

Lever, Inc. seeks an Engenheiro Dados in Brazil for a remote, senior data engineering role. You will transform complex datasets into reliable insights, designing data models, pipelines, and analytics environments using Python, SQL, Spark, Databricks, and cloud platforms.

Collaboration with business and technical teams drives scalable data products and data-driven decisions. The role emphasizes data quality, automation, predictive modeling, and evolving data architecture with modern BI tooling

Qualificações

• Bachelor's degree in a related field.
• Around 5 years of professional experience in data engineering or analytics.
• Strong knowledge of data modeling and data architecture concepts.
• Hands-on experience with SQL and programming languages such as Python, Scala, R, and/or Java.
• Experience with Apache Spark, Apache Airflow, Databricks, ETL/ELT processes, and Big Data technologies.
• Knowledge of Power BI, data visualization, and data storytelling.
• Understanding of BI, Data Warehousing, ETL, and modern data engineering practices.
• Knowledge of cloud environments, particularly AWS and/or Azure.
• Experience with Git, CI/CD, Azure DevOps, and infrastructure-as-code practices such as Terraform.
• Understanding of basic Machine Learning concepts and mathematical and statistical principles.
• Familiarity with data observability tools and data quality practices.
• Knowledge of Agile methodologies such as Scrum, Lean, and Kanban.
• Strong analytical, investigative, and problem-solving abilities, with attention to detail and a structured approach to complex challenges.
• Collaborative mindset, interpersonal skills, resilience, accountability, and strong organizational abilities.
• Enthusiasm for research, preparing reports, presenting findings, and continuously developing technical knowledge.
• Basic English proficiency is required.

Responsabilidades

• Identify, analyze, and interpret trends and patterns across complex datasets to support decisions.
• Design and implement data models including MER, Star Schema, and Snowflake structures.
• Develop, maintain, and optimize data pipelines using Apache Airflow and ETL/ELT processes.
• Build data solutions using Python, SQL, Scala, Spark, Databricks, and related tools.
• Support data quality initiatives by cleansing and validating datasets and indicators.
• Prepare datasets for predictive and prescriptive modeling and automation.
• Develop dashboards and data visualizations using Power BI and storytelling techniques.
• Optimize scripts and queries to improve performance and reliability.
• Manage code versioning and delivery with Azure DevOps, Git, CI/CD, and Terraform/IaC.
• Work with AWS and/or Azure cloud environments and evolve data architecture and standards.
• Document architecture patterns and data roadmaps; prioritize information needs with stakeholders.
• Provide technical support to project teams and data organization members.
• Follow health, safety, environmental, security, and organizational policies.

Conhecimentos

SQL

Python

Apache Spark

Airflow

Databricks

Power BI

AWS

Azure

ETL/ELT

Data Modeling

Data Warehousing

Git

CI/CD

Terraform

Data Quality

Agile

English

Formação académica

Bachelor's degree in Computer Engineering / CS

Ferramentas

Sqoop

SSIS

Descrição da oferta de emprego

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Engenheiro Dados based in Brazil.

This is a remote opportunity for a senior data professional responsible for transforming complex datasets into reliable insights and scalable data solutions.
You will design, develop, and optimize data models, pipelines, ETL/ELT processes, and analytics environments.
The role combines data engineering, advanced analytics, visualization, and cloud technologies to support data-driven decision-making.
You will work with tools such as Python, SQL, Apache Spark, Airflow, Databricks, Power BI, and cloud platforms.
Your work will contribute to data quality, automation, predictive modeling, and the continuous improvement of data architecture.
The environment values collaboration, analytical thinking, technical ownership, continuous learning, and practical problem-solving.
You will partner with business and technical teams to turn information needs into efficient, actionable data products.

Accountabilities

• Identify, analyze, and interpret trends and patterns across complex datasets, supporting business and technical decision-making.

• Design and implement data models, including MER, Star Schema, and Snowflake structures, aligned with project and product requirements.

• Develop, maintain, and optimize data pipelines using Apache Airflow and advanced ETL/ELT processes.

• Build data solutions using Python, SQL, Scala, Apache Spark, Databricks, Sqoop, SSIS, and related technologies.

• Support data quality initiatives by cleaning, validating, reviewing, and monitoring datasets, reports, and performance indicators.

• Prepare datasets for predictive and prescriptive modeling and contribute to advanced data analysis and automation.

• Develop dashboards and data visualizations using Power BI and apply storytelling techniques to communicate insights effectively.

• Optimize scripts, data components, and queries to improve performance, reliability, and operational efficiency.

• Manage code versioning and delivery practices using Azure DevOps, Git, CI/CD, and Terraform/IaC.

• Work with AWS and/or Azure cloud environments and contribute to the evolution of data architecture and technical standards.

• Support the definition and documentation of architecture patterns, technical guidelines, and project data roadmaps.

• Partner with management and business stakeholders to prioritize information and data needs.

• Provide technical support to project teams and other members of the data organization.

• Follow applicable health, safety, environmental, security, and organizational procedures and policies.

Requirements

• Bachelor's degree in Computer Engineering, Computer Science, Systems Analysis, Information Systems, or a related field.

• Around 5 years of professional experience in data engineering, analytics, Big Data, or related disciplines.

• Strong knowledge of data modeling, database design, data mining, and data architecture concepts.

• Hands‑on experience with SQL and programming languages such as Python, Scala, R, and/or Java.

• Experience with Apache Spark, Apache Airflow, Databricks, ETL/ELT processes, and Big Data technologies.

• Knowledge of Power BI, data visualization, and data storytelling.

• Understanding of BI, Data Warehousing, ETL, and modern data engineering practices.

• Knowledge of cloud environments, particularly AWS and/or Azure.

• Experience with Git, CI/CD, Azure DevOps, and infrastructure-as-code practices such as Terraform.

• Understanding of basic Machine Learning concepts and mathematical and statistical principles.

• Familiarity with data observability tools and data quality practices.

• Knowledge of Agile methodologies such as Scrum, Lean, and Kanban.

• Strong analytical, investigative, and problem‑solving abilities, with attention to detail and a structured approach to complex challenges.

• Collaborative mindset, interpersonal skills, resilience, accountability, and strong organizational abilities.

• Enthusiasm for research, preparing reports, presenting findings, and continuously developing technical knowledge.

• Basic English proficiency is required.

Benefits

• 100% remote work model.

• Full-time employment opportunity.

• Meal or food allowance.

• Discounts on courses, universities, and language institutions.

• Access to an online learning platform with free, regularly updated courses and certificates.

• Mentoring opportunities.

• Benefits program for medical consultations and examinations.

• Medical insurance.

• Dental insurance.

• Discounts and advantages at participating establishments.

• Travel benefits and discounts.

• Pet care benefits.

We appreciate your interest and wish you the best!