Data Developer (Azure/Databrics) Sênior

Jobgether; Brasil; Presencial; BRL 210 000 - 340 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Health and dental insurance

Meal and food allowances

Childcare assistance

Extended parental leave

Wellness program

Resumo da oferta

Jobgether is assisting a partner in Brazil to find a Senior Data Developer (Azure/Databricks). The role focuses on building scalable data pipelines using Azure Databricks, Python, and SQL, while shaping data architecture and governance to support analytics and AI initiatives.

You will collaborate with business and data science teams to deploy AI models in cloud environments and guide cloud migration efforts, ensuring robust data quality and scalable data solutions.

Qualificações

• Experience with Azure Data Services and Databricks in data engineering environments.
• Strong hands-on experience with Databricks and PySpark for distributed data processing.
• Practical experience with Medallion Architecture and analytical data layers.
• Advanced proficiency in Python and SQL for data manipulation and analysis.
• Experience implementing CI/CD processes and source-code versioning using GitHub.
• Strong knowledge of analytical data modeling and scalable data structures for large-volume environments.
• Experience in cloud migration projects involving data platforms and modern cloud architectures.
• Experience developing ETL/ELT processes and integrating large data volumes from multiple sources.
• Experience deploying AI/ML models in cloud environments, including Azure ML.
• Experience with AI projects and automation of data/ML pipelines.
• Knowledge of data governance and engineering best practices.
• Experience in financial services or regulated environments is a plus.
• Familiarity with Master Data Management (MDM) initiatives would be desirable.
• Familiarity with Databricks MLflow for model management would be a plus.
• Familiarity with Data Lake and Data Warehouse environments would be desirable.
• Strong analytical thinking and collaboration; ownership of decisions.

Responsabilidades

• Develop, maintain, and optimize ETL/ELT data pipelines in Azure using Databricks and PySpark.
• Contribute to data architecture decisions and evolve data models for scalability.
• Implement CI/CD practices to automate deployments and enable reliable code versioning in GitHub.
• Design and evolve Unity Catalog tables with governance and versioning practices.
• Collaborate with business and data science teams to deploy AI models in cloud environments.
• Ensure data quality through profiling, monitoring, and validation across pipelines.
• Document architectures, decisions, standards, and best practices for maintainability.
• Support cloud migration initiatives with secure and high-quality data architectures.

Conhecimentos

Databricks

PySpark

Python

SQL

GitHub

Azure Data Services

Azure ML

Medallion Architecture

Data Modeling

Data Governance

CI/CD

MLflow

Data Lake/Warehouse

MDM

Data Migration

Ferramentas

Databricks

GitHub

Descrição da oferta de emprego

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

This is a senior Data Engineering opportunity to build and evolve scalable data solutions within a technology-driven environment and a specialized financial services project. You will design, develop, and maintain robust ETL/ELT pipelines using Azure and Databricks, working with large volumes of data and modern cloud architectures. The role combines hands-on engineering with a broader 360-degree perspective, ensuring that technical decisions support the wider project and business objectives. You will contribute to cloud migration initiatives, data modeling, governance, CI/CD automation, and the deployment of AI models into production environments. Working closely with business and data science teams, you will help transform high-quality data into reliable analytical and AI capabilities. This position is ideal for a senior professional who enjoys solving complex data challenges and working with modern cloud, analytics, and AI technologies.

Accountabilities

• Develop, maintain, and optimize ETL/ELT data pipelines in Azure, leveraging Databricks and PySpark for large-scale data processing and integration.
• Apply a 360-degree perspective to data engineering initiatives, understanding the broader architecture and anticipating how individual technical decisions may affect the overall project.
• Implement CI/CD practices to automate deployments, improve development workflows, and maintain reliable code versioning through GitHub.
• Design, model, and evolve tables within Unity Catalog, following consistent naming conventions, schema versioning practices, and data governance standards.
• Design and optimize data models and analytical structures to support scalability, performance, reliability, and effective data consumption.
• Support cloud migration initiatives by contributing to secure, high-quality, and reliable data architectures while maintaining data integrity throughout the migration process.
• Collaborate with business stakeholders and data science teams to support the deployment and operationalization of AI models in cloud environments.
• Establish and maintain data quality practices, including data profiling, monitoring, validation, and consistency checks across data pipelines.
• Document data engineering processes, architectures, technical decisions, standards, and best practices to promote maintainability and knowledge sharing.

Requirements

• Solid professional experience working with Azure Data Services and Databricks in data engineering environments.
• Strong hands-on experience with Databricks and PySpark for distributed data processing and transformation.
• Practical experience with Medallion Architecture and analytical data layers, including ingestion, preparation, and consumption.
• Advanced proficiency in Python and SQL for data manipulation, transformation, integration, and analysis.
• Experience implementing CI/CD processes and source-code versioning using GitHub.
• Strong knowledge of analytical data modeling and experience designing scalable data structures for large-volume environments.
• Previous experience participating in cloud migration projects, preferably involving data platforms and modern cloud architectures.
• Solid experience developing ETL/ELT processes and integrating large volumes of data from multiple sources.
• Experience supporting the deployment of AI or Machine Learning models in cloud environments, including exposure to tools such as Azure Machine Learning.
• Experience with AI-related projects and the automation of data and machine learning pipelines.
• Strong understanding of data-oriented architectures, data governance, and engineering best practices is a plus.
• Experience in financial services or other highly regulated environments is considered an advantage.
• Familiarity with Master Data Management (MDM) initiatives is desirable.
• Experience with Databricks MLflow for model management and lifecycle tracking is a plus.
• Familiarity with Data Lake and Data Warehouse environments is desirable.
• Strong analytical thinking, collaboration skills, ownership, and the ability to understand the broader impact of technical decisions.

Benefits

• Health and dental insurance.
• Meal and food allowances.
• Childcare assistance.
• Extended parental leave.
• Access to fitness, health, and wellness professionals through Wellhub/Gympass and TotalPass partnerships.
• Profit-sharing program (PLR).
• Life insurance.
• Continuous learning opportunities through a dedicated corporate learning platform.
• Access to online health, mental health, and well-being resources.
• Pregnancy and responsible parenthood support programs.
• Partnerships with online learning and professional development platforms.
• Language-learning platform.
• Employee discount programs.
• Inclusive environment with dedicated health and well-being teams, inclusion specialists, and employee affinity groups.
• Additional salary, healthcare, leave, and employee benefits may be provided according to the partner company’s applicable policies.
• For candidates residing in the Campinas Metropolitan Region, regular presence at the local offices is required according to the applicable workplace policy.

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!

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.