Sênior Data Developer (Dabricks / MongoDB)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sênior Data Developer (Databricks / MongoDB) based in Brazil.

This role is designed for a senior data professional who will help build and evolve scalable data platforms supporting strategic business initiatives. The position involves designing, developing, and maintaining robust data pipelines using modern processing technologies and cloud environments. You will work with large-scale data processing, integration workflows, and advanced analytics solutions to enable better decision-making. The role combines engineering expertise, problem-solving, and collaboration with technology teams in a dynamic environment. You will contribute to improving data quality, performance, reliability, and accessibility across different business areas. This is an opportunity to work on impactful data transformation projects while applying best practices in data engineering, automation, and AI-enabled development.

Accountabilities:: The Senior Data Developer will be responsible for designing, implementing, and maintaining data engineering solutions that support scalable analytics and business operations. The role requires strong technical ownership, attention to data quality, and the ability to collaborate across teams to improve data platforms and processes.

Design, develop, and maintain scalable data pipelines for data ingestion, processing, transformation, and integration.

Build and optimize solutions using Databricks, Python, PySpark, Spark, and SQL.

Develop workflows that enable the availability of reliable data for business and technology consumers.

Work with structured and non-structured data sources, including relational databases and MongoDB environments.

Ensure the performance, scalability, reliability, and quality of data processing solutions.

Monitor pipelines and data processes, identifying and resolving operational issues proactively.

Implement performance improvements and contribute to the continuous evolution of data architecture.

Support data modeling, data treatment, and information delivery for different stakeholders.

Develop and maintain CI/CD practices, ensuring proper version control, testing, and code quality.

Collaborate on machine learning model operationalization and MLOps practices within data platforms.

Requirements:

The ideal candidate should have strong experience in data engineering, distributed processing, cloud environments, and modern data development practices. The role requires technical depth, analytical thinking, and the ability to build reliable solutions in complex data ecosystems.

Solid experience as a Data Engineer, Senior Data Engineer, or equivalent role.

Strong knowledge of Python applied to data engineering, automation, analytics, and AI-related solutions.

Advanced SQL skills and experience working with structured data exploration and manipulation.

Strong knowledge of MongoDB and non-relational database environments.

Hands-on experience with Databricks, PySpark, and Spark.

Experience building, optimizing, and supporting scalable data pipelines.

Experience working with cloud environments, preferably Azure Databricks.

Knowledge of near-real-time data processing, preferably with Kafka.

Experience deploying machine learning models in Databricks environments and applying MLOps practices.

Experience with CI/CD pipelines, especially GitHub and GitHub Actions.

Knowledge of data engineering best practices, including version control, testing, code reviews, and data quality management.

Familiarity with data modeling, ETL/ELT processes, Data Lakes, distributed processing concepts, and regulated environments is considered a plus.

Experience applying AI tools in development workflows, such as coding assistants, prompt engineering, or automated code reviews, is desirable.

Benefits:

Health and dental insurance.

Meal and food allowance.

Childcare assistance.

Extended parental leave.

Access to wellness and fitness partnerships through platforms such as Wellhub and TotalPass.

Profit-sharing program.

Life insurance.

Continuous learning platform with technical and professional development content.

Discounts through partner programs.

Online platforms focused on physical health, mental health, and overall well-being.

Pregnancy and responsible parenthood support programs.

Partnerships with online learning platforms.

Language learning platform.

Remote work flexibility.

Additional benefits according to company policies.

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