Data Engineer at Jobgether

, , Brazil -

Full Time

Start Date

Immediate

Expiry Date

13 Oct, 26

Salary

0.0

Posted On

15 Jul, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Microsoft Azure, Databricks, Apache Spark, Python, SQL, Delta Lake, CI/CD, DataOps, Data Modeling, Unity Catalog, Distributed Data Processing, Agile Methodology

Industry

Internet Marketplace Platforms

Description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer based in Brazil. This role offers the opportunity to design, develop, and optimize scalable data solutions that support critical business operations. You will work on modern data platforms, building reliable pipelines and workflows using advanced cloud technologies. The position focuses on transforming complex data challenges into efficient, high-performance engineering solutions. You will collaborate with cross-functional teams to improve data accessibility, quality, and operational efficiency. The environment values technical excellence, innovation, and continuous improvement through modern DataOps practices. This is an opportunity for an experienced data professional to influence architecture decisions and contribute to large-scale data initiatives. \n Accountabilities: The Data Engineer will be responsible for designing, implementing, and maintaining robust data platforms, ensuring scalability, reliability, and performance across complex data environments. Build, maintain, and optimize scalable data pipelines and workflows using modern data engineering technologies. Develop and manage data solutions within Databricks environments, including Delta Lake, Spark, Unity Catalog, Jobs, and Workflows. Design and tune distributed data processing systems to handle large-scale data workloads efficiently. Create and maintain complex data models across multiple business domains. Develop data processing solutions using SQL and programming languages, with a preference for Python expertise. Implement and improve CI/CD pipelines, DevOps/DataOps practices, automated testing, and engineering standards. Work with distributed processing technologies such as Apache Spark to support reliable data operations. Troubleshoot, debug, and resolve complex technical issues across multi-system environments. Collaborate with engineering, analytics, and business teams to deliver high-quality data solutions. Contribute to technical roadmaps and lead cross-functional engineering initiatives. Improve data observability, monitoring, quality processes, and platform reliability. Participate in Agile development practices, contributing to planning, collaboration, and continuous improvement. Requirements: The ideal candidate brings strong data engineering expertise, cloud experience, and the ability to design scalable solutions in dynamic technical environments. 5+ years of experience in data engineering or a related technical field. Strong hands-on experience with Microsoft Azure data services. Extensive experience working with Databricks and building production-grade data pipelines. Advanced SQL skills and proficiency in at least one programming language, preferably Python. Strong experience with Apache Spark and distributed data processing architectures. Proven ability to design, implement, and optimize scalable data workflows. Experience with data modeling across multiple business areas. Strong knowledge of version control, CI/CD pipelines, DevOps/DataOps practices, and automated testing. Strong analytical, debugging, and problem-solving skills. Ability to collaborate effectively within Agile, cross-functional engineering teams. Strong communication skills and ability to influence technical decisions. Additional experience that would be valued: Experience with Databricks Unity Catalog, Delta Live Tables, and Databricks Workflows. Experience with DataOps practices, including pipeline monitoring, observability, and automated quality checks. Knowledge of metadata management and cataloging platforms such as Purview, Collibra, or Alation. Experience with streaming technologies such as Kafka, Event Hubs, or Kinesis integrated with Spark Structured Streaming. Experience working in Agile environments. Benefits: Fully remote work model, allowing professionals to work from anywhere in LATAM. Full-time contract opportunity with an initial duration of 5+ months and potential extension. Flexible remote collaboration environment. Opportunity to work with modern cloud data technologies and large-scale engineering challenges. Exposure to advanced DataOps, analytics, and distributed data processing practices. Collaboration with experienced technical teams in an innovative environment. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1

Responsibilities

Design, implement, and maintain scalable data platforms and pipelines using Databricks and Azure. Collaborate with cross-functional teams to optimize data accessibility, quality, and operational efficiency through DataOps practices.