Data Developer Senior

Jobgether; Brasil; Hybride; BRL 180 000 - 320 000; Plein temps

Avantages offerts par ce poste

Health insurance

Meal allowances

Childcare assistance

Parental leave

Wellness programs

Profit-sharing

Résumé du poste

Jobgether, in Brazil, seeks a Senior Data Developer to lead data engineering efforts, shaping architecture and standards. You will guide engineers and analysts, build robust pipelines with Azure Databricks and Delta Lake, and ensure data quality and governance across the organization.

You will translate complex business needs into scalable data solutions, collaborate with product and operations, and drive continuous improvement in data platforms from Bronze to Gold layers.

Qualifications

• Extensive leadership in data engineering or mentoring data teams.
• Experience with financial-sector KPIs and banking indicators.
• Advanced SQL and strong Python/PySpark proficiency.
• Hands-on Azure Databricks, Spark, PySpark, and Spark SQL.
• Practical experience with Azure Data Factory to orchestrate data pipelines.
• Knowledge of Medallion architecture (Bronze/Silver/Gold) and Delta Lake.
• Experience designing analytical data models (star schemas, OBT, facts/dimensions).
• Familiarity with data governance, data quality, pipeline documentation, and traceability.
• Ability to communicate technical concepts to varied stakeholders.
• Experience prioritizing backlogs within agile teams.

Responsabilités

• Provide technical guidance to data engineers and analysts, promoting best practices.
• Design and evolve data platform architecture with standard data models and governance.
• Ensure architecture scalability, maintainability, and alignment with business needs.
• Refine technical requirements, acceptance criteria, and implementation plans.
• Establish and maintain data quality and traceability across the data lifecycle.
• Develop and review data solutions using SQL, Python, PySpark, and Azure technologies.
• Build and orchestrate data pipelines using Azure Databricks, Data Factory, Spark, and Delta Lake.
• Create analytical data models including star schemas and OBT structures.
• Collaborate with stakeholders to deliver reliable financial KPIs and reporting.

Connaissances

Data engineering leadership

Advanced SQL

Python

PySpark

Azure Databricks

Azure Data Factory

Delta Lake

Data modeling

Data governance

Agile backlog management

Outils

Azure Databricks

Azure Data Factory

Delta Lake

Description du poste

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

Join a technology-driven team focused on building reliable, scalable, and high-quality data solutions that support strategic business decisions. In this senior role, you will help shape data architecture, establish engineering standards, and guide the technical development of data engineers and analysts. You will work with modern cloud technologies, including Azure Databricks, Azure Data Factory, and Delta Lake, to build robust data pipelines and scalable data platforms. Your expertise will help ensure data accuracy, governance, traceability, and accessibility across the organization. Collaborating with product, operations, and business stakeholders, you will translate complex requirements into practical data solutions. This opportunity is ideal for an experienced data professional who combines technical leadership, architectural vision, and a strong commitment to continuous improvement.

Accountabilities

• Provide technical guidance to data engineers and analysts, promoting engineering best practices, conducting technical reviews, and supporting the continuous improvement of data solutions.
• Design, structure, and evolve the data platform architecture, defining standards for data modeling, pipelines, governance, and Bronze, Silver, and Gold data layers.
• Ensure data architecture remains consistent, scalable, maintainable, and aligned with business and analytical requirements.
• Support the prioritization and refinement of technical demands, ensuring backlog items and user stories have clear requirements, acceptance criteria, and feasible implementation plans.
• Establish and maintain data quality practices, including validation, documentation, and traceability throughout the data lifecycle.
• Develop and review data engineering solutions using advanced SQL, Python, PySpark, and Azure-based technologies.
• Build, optimize, and orchestrate data pipelines using Azure Databricks, Azure Data Factory, Spark, Spark SQL, and Delta Lake.
• Design and maintain analytical data models, including star schemas, one big table (OBT) structures, and fact and dimension models.
• Support the reliable delivery of financial-sector KPIs and indicators, ensuring consistency and accuracy in reporting and analytics.
• Act as a technical point of contact for stakeholders across product, operations, and management, translating strategic objectives into effective data solutions.
• Collaborate with multidisciplinary teams to improve data governance, technical processes, and the overall performance of the data platform.

Requirements

• Extensive experience in data engineering, including technical leadership or mentoring of data engineering teams.
• Experience working with financial-sector KPIs and banking-related indicators.
• Advanced SQL skills and strong proficiency in Python and PySpark for developing, reviewing, and optimizing data solutions.
• Hands‑on experience with Azure Databricks, including Spark, PySpark, and Spark SQL.
• Practical experience using Azure Data Factory (ADF) to orchestrate and manage data pipelines.
• Strong knowledge of Medallion architecture, including Bronze, Silver, and Gold layers, and experience working with Delta Lake.
• Experience designing and implementing analytical data models, including star schemas, OBT structures, and fact and dimension tables.
• Knowledge of data governance, data quality management, pipeline documentation, and data traceability.
• Ability to communicate technical concepts clearly to both technical and non-technical stakeholders.
• Experience managing and prioritizing technical backlogs within agile teams.
• Strong analytical thinking, problem-solving skills, attention to detail, and the ability to balance architectural decisions with practical delivery needs.
• A collaborative mindset and the ability to guide teams while maintaining high standards of technical quality.

Nice to have:

• Experience with Azure Purview or other data catalog and lineage tools.
• Familiarity with data CI/CD practices and tools such as Azure DevOps.
• Knowledge of business intelligence platforms such as Power BI or Looker for validating KPIs and analytical outputs.
• Experience supporting growth marketing teams with customer acquisition, activation, and retention analytics.
• Knowledge of data streaming technologies, including Spark Structured Streaming or Azure Event Hubs.
• Relevant Azure or Databricks certifications, such as DP-203 or Databricks Certified Data Engineer.
• Experience delivering large-scale, business-critical data projects.
• Knowledge of generative AI applications in data engineering and analytics.

Benefits

• Comprehensive health and dental insurance.
• Meal and food allowances.
• Childcare assistance.
• Extended parental leave.
• Access to fitness and wellness programs through Wellhub and TotalPass.
• Profit-sharing program (PLR).
• Life insurance.
• Continuous learning opportunities through an internal learning platform.
• Partnerships with online learning platforms and professional development courses.
• Language-learning resources.
• Employee discount programs.
• Free online resources supporting physical health, mental well-being, and overall wellness.
• Courses focused on pregnancy, parenting, and responsible family care.
• An inclusive workplace with dedicated health, wellness, and inclusion teams.
• Remote work within Brazil, with office attendance required for professionals residing in the Campinas metropolitan area, according to the applicable attendance policy.
• Salary: Compensation details were not specified in the original job description.