Source-listed Job

Mid Data Engineer

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Mid Data Engineer based in Brazil.

Job Remote Source description available
Jobgether Source published Oct 14, 2026 Source retrieved Oct 14, 2026
Source: jobgether (lever) · A retrieval date records when our system last obtained the source record. It does not guarantee the vacancy is still open or that every detail has been independently checked.
Description from the source The source description is formatted below for discovery. The provider owns the original wording and may change its requirements or close applications.
EmploymentFull-time
Work modeRemote / location-flexible

Overview

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Mid Data Engineer based in Brazil.

Full job description

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Mid Data Engineer based in Brazil. Join a collaborative, international Data & Analytics team focused on building scalable data solutions that turn complex information into actionable business insights. In this role, you will develop and optimize data pipelines, manage data transformations, and support analytics initiatives using modern cloud-based data technologies. You will work with Databricks, Python, SQL, and PySpark to ensure reliable data integration and processing across the data lifecycle. Partnering with technical and business stakeholders, you will help translate analytical needs into efficient, high-quality data solutions. You will also contribute to dashboards, reporting, and advanced analytics initiatives in an Agile environment. This is an opportunity to grow your technical expertise while supporting data-driven decision-making across international projects.

Develop, maintain, and optimize ETL pipelines using Databricks to support efficient data ingestion, integration, and processing. Collaborate with technical teams and business stakeholders to gather requirements and design scalable data solutions. Manage the data lifecycle, from ingestion into the data lake through bronze, silver, and gold layers to preparing datasets for reporting and visualization. Implement and maintain data transformation, processing, and automation logic using SQL, Python, and PySpark. Support advanced analytics initiatives and machine learning operations within the Databricks environment. Build, maintain, and improve dashboards and reports, with Sigma Computing as a preferred visualization platform. Apply Agile methodologies to improve collaboration, delivery efficiency, and continuous improvement across the analytics team. Investigate complex data challenges, identify opportunities for optimization, and implement effective solutions. Requirements: Bachelor’s degree in Computer Science or a related field. At least three years of experience as a Data Engineer, Analytics Engineer, or in a similar role. Advanced proficiency in SQL and Python for data transformation, processing, and automation. Practical experience with PySpark and Databricks or other data lake platforms. Familiarity with the medallion architecture, including bronze, silver, and gold data layers. Experience developing ETL pipelines and supporting machine learning operations. Strong analytical thinking and problem-solving skills, with an understanding of advanced analytics techniques. Familiarity with Agile methodologies and collaborative development practices. Excellent communication skills and the ability to work effectively with both technical and non-technical stakeholders. Nice to have: Familiarity with Sigma Computing, experience with data visualization tools such as Qlik or similar platforms, knowledge of AI and machine learning frameworks, and experience with R. Benefits: Professional development: Opportunities to strengthen technical skills through challenging projects and ongoing learning. International exposure: The chance to collaborate with international clients and distributed engineering teams. Collaborative environment: Work alongside professionals who value knowledge sharing, teamwork, and innovation. Career growth: Access to career development pathways and mentorship programs. Remote work: The position is advertised as remote; confirm eligibility and any location-specific arrangements for Brazil during the application process.

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