Data Engineer

• Work with one of our U.S.-based clients.
• Develop and implement data pipelines using PySpark.
• Collaborate with cross-functional teams including machine learning engineers, software developers, analytics engineers, and product managers.
• Translate business requirements into highly available data solutions.
• Maintain and improve existing data pipelines and systems.

Lead Data Engineer

• Develop and optimize high-performance data pipelines.
• Design scalable solutions for processing large volumes of data.
• Contribute to the definition and evolution of the data architecture.
• Implement ETL processes and integration across multiple data sources.
• Work with distributed systems and event-driven architectures.
• Ensure data quality, performance, and reliability.
• Integrate data platforms with applications and APIs.
• Participate in technical discussions and support the evolution of engineering best practices.

Senior Data Engineer, Spark

• Leega is a company dedicated to providing efficient, innovative service to its clients — and our greatest asset is our people. Our culture is inspiring and our values guide daily life: ethics and transparency, commitment to quality, teamwork, economic, social and environmental responsibility, human relations, and credibility. We seek innovative professionals who are motivated by challenges and focused on results. If you are looking for a dynamic, supportive company that invests in employees through continuous training, Leega is the place for you! >> LEEGA IS FOR EVERYONE — we will be very happy to have you on our team. Come be part of our story and help build our future. Register for our openings now!

Senior Data Architect – Google Cloud Platform, Databricks

• Design and implement the dbt platform architecture on Databricks (Unity Catalog, medallion layers: bronze/silver/gold).
• Structure the dbt project: modeling standards, naming conventions, layers (staging/intermediate/marts), macros, tests, and documentation.
• Build CI/CD pipelines for dbt (validation, build, tests, deploy per environment — dev/staging/prod).
• Automate provisioning and operations using IaC (Terraform) and DevOps practices.
• Optimize cost and performance (clusters, SQL Warehouses, Photon, partitioning, incremental processing).
• Define data governance and security (Unity Catalog, access control, masking of sensitive data).
• Mentor the team on analytical engineering best practices and review code (PRs).

Senior Data Engineer – Databricks, DBT

• Atuar na construção, manutenção e evolução de soluções de dados e analytics no ecossistema Azure
• Desenvolver, automatizar e monitorar pipelines de ingestão, transformação e disponibilização de dados
• Modelar bases analíticas para consumo em Power BI e Qlik
• Criar e manter dashboards, painéis gerenciais e relatórios analíticos com foco em performance, usabilidade e visão executiva
• Traduzir necessidades de negócio em indicadores, métricas e análises acionáveis
• Garantir a qualidade, integridade e governança dos dados ao longo de todo o fluxo
• Trabalhar em parceria com times de tecnologia, negócio, controladoria, operações e liderança
• Identificar oportunidades de melhoria em processos, automações e arquitetura de dados
• Apoiar a definição e padronização de KPIs, regras de negócio e documentação técnica/funcional
• Atuar na sustentação e evolução do ambiente de BI, promovendo boas práticas de modelagem e visualização.

Engenheiro de Dados Sênior

• Desenvolver, manter e evoluir soluções de engenharia de dados, garantindo qualidade, disponibilidade e performance dos dados.
• Construir e otimizar processos de ingestão, transformação e disponibilização de dados.
• Desenvolver e manter rotinas utilizando SQL e linguagens de programação aplicadas ao contexto de dados.
• Atuar na modelagem de dados e na implementação de boas práticas de desenvolvimento.
• Utilizar ferramentas de versionamento de código, realizando controle e gestão de alterações em ambientes colaborativos.
• Desenvolver e manter pipelines de CI/CD para automação de processos de entrega.
• Trabalhar com serviços AWS, especialmente Amazon Redshift e Amazon S3, apoiando a construção e sustentação das soluções de dados.
• Participar de discussões técnicas, análises de requisitos e definição de soluções alinhadas às necessidades do negócio.
• Monitorar e atuar na melhoria contínua da performance e confiabilidade dos ambientes de dados.
• Híbrido (1x por semana presencial na Faria Lima para quem reside em São Paulo).

Engenheiro de Dados – Pl.

• Develop and maintain robust, scalable data pipelines.
• Design and support Data Warehouse, Data Lakehouse, and streaming environments.
• Define data architecture standards, best practices, and cloud cost management.
• Work on integrating multiple corporate data sources.
• Support BI and business teams in data consumption and analysis.

Development Analyst – Data Engineer

• Plan and execute business-side data migration activities for Finance data objects in line with global, deployment, and country-specific requirements and timelines.
• Perform and coordinate data cleansing activities, ensuring completion within agreed schedules and quality standards.
• Complete data collection activities for manual and construction data objects.
• Collaborate with IT teams to prepare, validate, and maintain value mappings between source and target systems.
• Create and maintain master data lists for assigned Finance data objects where applicable.
• Provide business insights and detailed information to technical teams to support data extraction and conversion from legacy systems.
• Work closely with IT teams and Business Data Owners to identify and confirm country-specific data objects in scope.
• Ensure data readiness and data quality throughout the entire migration lifecycle for assigned Finance data objects.
• Verify that data is fit for purpose and aligned with business requirements and stakeholder expectations.
• Review and formally approve upload files before and after data loads.
• Perform manual (type-in) data loads into target systems where required. • Execute dual maintenance activities to ensure data consistency across systems.
• Execute and approve data verification scripts and validation activities.
• Act as the functional Single Point of Contact (SPoC) for assigned Finance data objects during migration and Hypercare phases.
• Support defect management activities, ensuring timely resolution of data related issues.

Business Data Migration Consultant – Finance, SAP

• Work on SAP rollout and data migration projects.
• Plan, execute, and validate master and transactional data migration activities.
• Perform data mapping, transformation, loading, and reconciliation.
• Ensure data quality and integrity throughout the migration process.
• Propose improvements and optimizations to migration processes.
• Work with external systems responsible for master data.
• Produce functional documentation and training materials.

SAP Data Migration Consultant – Senior

• Continuously monitor batch, streaming and on-demand data pipelines to ensure availability and data quality.
• Identify, analyze and resolve operational incidents and critical failures in data environments.
• Perform advanced troubleshooting by analyzing logs, metrics and alerts on GCP platforms.
• Monitor and support data workflows, including DAGs, reprocessing, dependencies, and load validations.
• Track execution of processes in Dataproc, Spark, BigQuery and other components of the data architecture.
• Collaborate with Data Engineering, Architecture, Governance and Business teams to resolve issues and drive continuous improvements.
• Contribute to the stability, reliability and evolution of data environments.
• Prepare and maintain incident documentation, root cause analyses (RCA), operational procedures and action plans.
• Participate in automation, observability and operational process optimization initiatives.

Senior Data Engineer – DBT

• Administration and optimization of relational and NoSQL databases in cloud environments (AWS/GCP)
• Ensuring high availability, performance and security of the environments
• Working with MySQL/Aurora, PostgreSQL, DynamoDB, Redis and Amazon RDS
• Performing tuning, monitoring, backup, restore and disaster recovery
• Supporting data platforms (S3, Athena, Data Lake)
• Troubleshooting incidents and automating operational routines
• Applying SRE best practices to ensure stability and scalability

Senior DBA – Cloud & Data Platforms

• Participate in the technical refinement of data cards, helping to map sources, transformation rules and destinations before development.
• Develop and maintain ETL/ELT pipelines using Python and SQL.
• Implement data capture strategies: full load, incremental by timestamp and Change Data Capture (CDC).
• Build and organize data into Raw + Trusted + Refined layers, respecting data contracts and governance standards.
• Integrate flows into pipeline orchestration (DAGs).
• Perform data quality validations: volume checks, nulls and duplicates before deployment.
• Document data flows, architectural decisions and system dependencies.

Junior Data Engineer

• Data Integration and Collection: Aggregates structured, semi-structured and unstructured data from multiple sources (databases, APIs, files);
• Real-time and Batch Data Ingestion: Designs scalable ingestion architectures using Pub/Sub for streaming and Cloud Storage/Dataflow for batch processing, ensuring data integrity in BigQuery;
• Data Processing and Transformation: Builds pipelines to transform raw data with standardization, deduplication, filtering and enrichment processes;
• Governance and Operations: Manages orchestration via Cloud Composer with a focus on idempotency and resilience, implements proactive monitoring (logs/alerts) and technical documentation to ensure continuity and maintainability of solutions;
• Performance Optimization: Leads FinOps initiatives, optimizing BigQuery slot utilization, storage costs and job efficiency in Dataflow/Dataproc to reduce TCO (Total Cost of Ownership);

Senior Data Engineer

• Develop, maintain, and optimize data ingestion, processing, and transformation pipelines.
• Work on structuring and managing Bronze, Silver, and Gold data layers.
• Implement data integration and data provisioning processes using Denodo.
• Work on data modeling for analytical and enterprise environments.
• Ensure data quality, integrity, and governance.
• Support business and technology teams in building data-driven solutions.
• Monitor and optimize the performance of loads and queries in BigQuery environments.
• Participate in architectural decisions and best practices related to data engineering.

Mid-level Data Engineer, GCP

• Build and support data pipelines that can handle the volume and complexity of data while ensuring scale, data accuracy, availability, observability, security, and optimum performance
• Developing and maintaining data warehouse tables, views, and models, for consumption by analysts and downstream applications
• Own and lead workstreams while driving results through self or your team
• Participate in periodic data engineering activities, e.g. monthly insights reporting, profile data updates, etc
• Troubleshoot production issues, and participating in on-call activities
• Identify several areas for improving data engineering processes, and share with the team
• Contribute consistently towards building our data platform, which includes data pipelines, and data warehouse layers
• Independently own and lead workstreams whether it is periodic data engineering activities, or work items in support of our roadmap
• Deepen your understanding, and build subject matter expertise of our data & ecosystem
• Your contributions have led to us making significant progress in implementing the data platform strategy, and key data initiatives to support the company's growth
• You’ve established yourself as a key team member with subject matter expertise within data engineering

• Organizar, coletar e processar (ferramentas ETL) grandes volumes de dados, traduzindo os objetivos de negócios do cliente em uma estratégia de gerenciamento de informações e inteligência de negócios.
• Responsável por manter os pipelines de dados e garantir a segurança no acesso as informações.
• Sua atuação pode abranger a criação e exposição de métricas (painéis) sobre os dados obtidos, garantindo assim qualidade, e integridade a estas informações.

• Responsible for the maintenance, deployment and evolution of Big Data solutions, working in environments that process large volumes of data.
• Ensure the performance, reliability and scalability of applications, as well as support consumers of data solutions and collaborate with multidisciplinary teams in an agile environment.
• Monitor deployments and provide support to consumers of data solutions.
• Develop and maintain large-scale data processing pipelines.
• Identify and resolve issues related to application performance and reliability.
• Implement and optimize solutions using Big Data technologies.
• Participate in defining architectures and strategies for data processing and storage.
• Work together with multidisciplinary teams to deliver innovative solutions.
• Support continuous improvement initiatives and process automation.
• Operate following agile methodologies, participating in Scrum ceremonies.

Data Engineer, Big Data – Senior

• You will architect and evolve the datalake that is the company's data nervous system — the foundation that feeds, in real time, the dynamic pricing engine, ML models, and the group's business intelligence.
• This is an ownership role: you define the multi-tenant Lakehouse architecture, from streaming to the semantic layer, and are responsible for its reliability, governance, and cost.
• Design and evolve the data lake on Apache Iceberg over S3 — well-defined layers, partitioning and compaction, time-travel and support for DELETE/UPDATE for LGPD (Brazilian data protection law).
• Build real-time ingestion (Kafka, Flink, CDC with Debezium) with controlled schema evolution (Schema Registry) and delivery guarantees.
• Model the transformation layer in dbt and orchestrate batch and quality flows in Airflow, from crawler to backfill.
• Maintain metric definitions in Cube.js — the single source that feeds BI and AI agents and ensures consistency across the company.
• Operate federated and low-latency OLAP queries over the lake, with cost and access isolation by tenant and performant queries.
• Ensure data testing, lineage and cost efficiency, keeping the platform reliable as it scales.

• Develop and maintain data ingestion, transformation, and publishing pipelines (ETL/ELT).
• Integrate data from different systems, formats, and domains.
• Implement versioning, lineage, and data validation mechanisms.
• Ensure performance, monitoring, reliability, and cost control of data flows.
• Automate processes and support the continuous operation of data environments.
• Support data science and AI teams by providing analysis-ready data.
• Document pipelines and support knowledge transfer.

• Develop data ingestion pipelines in Azure Data Factory and implement transformations in Databricks/DBT, ensuring consistency and traceability.
• Migrate data flows from legacy architectures to the current layered architecture (bronze, silver and gold).
• Monitor and maintain existing pipelines, troubleshooting failures in Azure Data Factory, Databricks and Synapse to prevent disruptions to critical processes. Implement data quality routines (integrity, completeness, accuracy) and record evidence.
• Maintain and evolve data flows for specific business areas (e.g., commercial stockouts), ensuring delivery of strategic indicators.
• Create and maintain technical documentation for pipelines, flows and integrations in the Azure DevOps Wiki, Visio and OneNote.
• Log activities in Azure DevOps, supporting time tracking and demand monitoring.
• Map business processes (AS IS / TO BE), supporting data-related digital transformation initiatives.

See all jobs on JobTailor

Lead Data Engineer

Senior Data Engineer, Spark

Senior Data Architect – Google Cloud Platform, Databricks

Senior Data Engineer – Databricks, DBT

Engenheiro de Dados Sênior

Engenheiro de Dados – Pl.

Development Analyst – Data Engineer

Business Data Migration Consultant – Finance, SAP

SAP Data Migration Consultant – Senior

Senior Data Engineer – DBT

Senior DBA – Cloud & Data Platforms

Junior Data Engineer

Senior Data Engineer

Mid-level Data Engineer, GCP

Senior Data Engineer

Engenheiro de Dados Sênior

Data Engineer, Big Data – Senior

Senior Data Engineer

Senior Data Engineer

Data Engineering Analyst II