Data Engineer I – Digital and IT Governance

Jobtailor; Goiânia; Presencial; BRL 120 000 - 240 000; Tempo integral

Resumo da oferta

Jobtailor is seeking a data engineering professional to support data availability, build large Big Data repositories, and develop scalable data architectures. You will implement data pipelines and collaborate with analysts to extract insights under supervision.

The role emphasizes secure data sharing, data quality, and adherence to corporate policies while enabling predictive and prescriptive modeling.

Qualificações

• Bachelor's degree in Computer Science or related field.
• Experience with data analysis programming languages, ETL and data modeling.
• Familiarity with Data Warehouse concepts and data processing architectures.

Responsabilidades

• Support making data available for analysis in a secure manner.
• Assist in building large repositories for Big Data.
• Develop, test and maintain databases and large-scale data processing systems.
• Enable Data Analysts to apply analytical techniques and extract insights.
• Prepare data for predictive and prescriptive modeling under supervision.
• Monitor and process variables rapidly, under direct supervision.
• Deploy analytical programs, ML and statistical methods of lower complexity.
• Identify opportunities to improve data reliability, efficiency and quality.

Conhecimentos

Python

R

Java

SQL

MongoDB

Scala

Hadoop

Spark

Data Warehouse

Data Processing Architectures

Formação académica

Bachelor's degree

Ferramentas

Oracle Databases

APIs

Descrição da oferta de emprego

• Support making data available for analysis in a secure manner
• Assist in building large repositories for Big Data
• Develop, test and maintain architectures such as databases and large-scale data processing systems
• Enable Data Analysts to apply analytical techniques and extract relevant insights
• Perform data collection, storage and distribution processes of low complexity
• Design lower-complexity solutions based on databases
• Create and define lower-complexity data pipelines
• Implement agile methodologies and use technologies to improve decision-inking, under direct supervision
• Prepare data for predictive and prescriptive modeling, under direct supervision
• Monitor and process variables rapidly, under direct supervision
• Deploy analytical programs, machine learning and statistical methods of lower complexity
• Identify ways to improve data reliability, efficiency and quality, under direct supervision
• Search for hidden patterns using data
• Identify and define new process improvement opportunities, under direct supervision
• Care for equipment, resources and materials under your responsibility and maintain the work environment
• Comply with rules, procedures, internal regulations, corporate policies and workplace safety standards

Requirements

• Required knowledge: data analysis programming languages; ETL; data modeling; Data Warehouse; principles and patterns of data processing architectures; database architecture; Oracle databases; integrations (APIs); Python; R; Java; SQL; Big Data; MongoDB; Scala; Hadoop; Spark
• Required education: Completed higher education (Bachelor's degree)
• Required field of study: Computer Science, Systems Analysis or related areas
• Preferred education: (not specified)
• Preferred field of study: (not specified)

Core Competencies

Demonstrates expertise in data analysis programming languages, ETL processes, and data modeling to support the development and maintenance of data architectures. Proficient in deploying machine learning and statistical methods while ensuring data reliability and compliance with corporate policies.

Highest-signal resume keywords

• Data Analysis Programming Languages
• ETL
• Data Modeling
• Database Architecture
• Big Data

Hard Skills

• Python
• R
• Java
• SQL
• MongoDB
• Scala
• Hadoop
• Spark
• Data Warehouse
• Data Processing Architectures

Industry Keywords

• Data Analysis
• Data Collection
• Data Storage
• Data Distribution
• Predictive Modeling
• Prescriptive Modeling
• Process Improvement
• Workplace Safety Standards

Tools & Technologies

• Oracle Databases
• APIs