Data Engineer

Location

Santos, SP | Brazil

Job description

Position Summary: Play a key role in structuring, organizing and optimizing data within an organization. Responsible for developing, building, testing and maintaining data architectures and systems. Acting in the integration of information from various sources, ensuring its availability, reliability, security and efficiency for analysis and application. Requirements: Degree in Computer Engineering, Computer Science, Data Engineering or related areas. Postgraduate and/or MBA degree desirable; Fluent English essential; ITIL certification or knowledge of its application within organizations; Experience with cloud ecosystems and architectural frameworks Knowledge of financial and budgetary models in order to estimate the financial impact of technical infrastructure alternatives. Technical Experience: Knowledge of SQL and NoSQL databases, experience in programming languages such as Python, R or Scala, understanding of Big Data tools (such as Spark), skills in data manipulation and visualization. Background on Microsoft .NET and Angular programing frameworks, Reporting tools such as Crystal Reports, Power BI, SSRS. Experience on Microsoft Azure Hosting, Synopsis, Devops tools Analytical skills: Ability to understand business requirements and turn them into viable data solutions, aptitude for statistical analysis and problem-solving skills. Understanding of IT Infrastructure: Familiarity with cloud concepts, knowledge of distributed systems and notions of information security. Excellent Communication Skills: Ability to communicate complex data analysis results clearly and effectively to different audiences. Leading IT Projects by orienting, training, planning, monitoring, and communicating requests to other IT colleagues. To work closely and actively with Business Users to ensure all deliverables are properly prioritized and managed to accomplish corporate strategies and timelines. Responsibilities: Data Engineer: Develop and implement solutions for data collection, storage, processing and distribution. ETL (Extract, Transform, Load): Create data pipelines to collect information from different sources, transform it into a suitable format and load it into the target systems. Data Integrations: In addition to the ETLs, creating, designing and maintaining interfaces to exchange data among different systems using methods and techniques such as APIs, file sharing, etc. Data Modeling: Design and create efficient data models, dimensional or relational, to meet analysis and query needs. Maintenance and Optimization: Monitor the performance of data systems, identify bottlenecks and make adjustments to improve efficiency, scalability and reliability. Security and Privacy: Implement security measures to protect data from unauthorized access, ensuring compliance with regulations and privacy policies. Interdepartmental Collaboration: Work closely with analytics teams, software engineering and other departments to understand data needs and provide appropriate solutions. Tool Development and Automation: Create tools and scripts to automate data manipulation, cleansing and analysis processes.

Job tags

Salary