Staff Data Engineer (São Paulo Brazil)
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Job Summary
We are seeking an experiencedStaff Data Engineer-Ito join theNPS Prismengineering team a Bain platform that provides advanced analytics benchmarking and insights into customer experience metrics across industries.
As a senior technical leader you willbe responsible fordesigning building andoptimizinglarge-scale high-performance data pipelines and architectures that power NPS Prisms analytics and client-facing applications. This role requiresdeep DatabricksexpertiseproficiencyinPython SQL andPySpark and the ability to work acrosscloud-native environments(Azure AWS or GCP).
Youllcollaborate closely with data scientists product managers and business stakeholders to shape and execute the platforms data strategy ensuring data quality scalability and reliability at enterprise scale.
Key Responsibilities
Data Architecture & Engineering Leadership
Design and own scalable data architectures for ingestion transformation and analytics onDatabricks.
Build robust ETL/ELT pipelines usingPySparkSQL andDatabricks Workflows.
Lead performance tuning partitioning and data optimization across large distributed systems.
Mentor junior data engineers and enforce best practices for code quality testing and version control.
Cloud & Platform Engineering
Develop andmaintaindata lakes and data warehouseson cloud platforms (Azure Data Lake AWS S3 GCPBigQuery etc.).
UtilizeAzure Data FactoryAWS Glue or similar orchestration tools to manage large-scale data workflows.
Integrate multiple data sources (structured semi-structured and unstructured) into unified models for NPS Prism analytics.
Databricks & Advanced Analytics Enablement
LeverageDatabricksfor large-scale data processing Delta Lake management and ML/AI enablement.
Drive the adoption ofDatabricks Unity Catalog governance and performance features.
Partner with analytics teams to enable seamless model training and inference pipelines on Databricks.
Data Quality Observability & Governance
Define and implement frameworks fordata validationmonitoring anderror handling.
Collaborate with platform teams toestablishdata lineage and governance using tools likeGreat ExpectationsMonte Carlo or Databricks-native observability.
Ensure compliance with Bains data security and privacy standards.
DevOps & CI/CD for Data
Implement CI/CD pipelines for data code deployments usingGitAzure DevOps orJenkins.
Automatetesting deployment andmonitoring fordata workflows to ensure reliability and repeatability.
Cross-Functional Collaboration
Work with product and business teams to translate analytical requirements into scalable technical designs.
Collaborate with Data Science and BI teams to deliver analytics-ready datasets for dashboards and models.
Serve as a technical advisor in architectural reviews and strategic data initiatives within NPS Prism.
Required Skills and Qualifications
Core Technical Expertise:
AdvancedproficiencyinDatabricks(mandatory).
Strong command ofPythonSQL andPySparkfor big data processing.
Experience withDelta LakeSpark optimization andcluster management.
Hands-on withETL/ELT designdatalakeandwarehouse architecture.
CloudexpertiseinAzureAWS orGCP(Azure preferred).
Leadership & Architecture:
68years of data engineering experience with at least 3 years in a lead or staff-level role.
Proven ability to design end-to-end data solutions and influence engineering best practices.
Strong mentorship and stakeholder management skills.
Additional Desirable Skills:
Familiarity withstreaming frameworks(Kafka Event Hubs).
Understanding ofdata modelingandBI integration(Power BI Tableau).
Exposure toDevOpsCI/CD pipelines andInfrastructure as Code (IaC).
Strong problem-solving and analytical skills.
Educational Qualifications
Bachelors orMasters degree inComputer ScienceInformation Systems ora relatedfield.
Required Experience:
Staff IC
Key Skills
- Computer Science
- Docker
- Kubernetes
- Python
- VMware
- C/C++
- Go
- System Architecture
- gRPC
- OS Kernels
- Perl
- Distributed Systems
About Company
NPS Prism provides actionable voice-of-the-customer insights from your own and your competitors’ customers. Start making the improvements they care about most.
