Intermediate Data Platform Engineer

Há 5 dias

Vitoria, Brasil Elios Talent Tempo inteiro

Data Platform Engineer – Intermediate
Key Highlights
️ Build and expand core data platform components powering analytics, experimentation, and algorithm development
⚡ Develop scalable ETL, streaming, and metadata systems using Spark, Kafka, and modern lakehouse technologies
Support high-volume data transformation, federated querying, and performance optimization
Strengthen RBAC, data governance, and secure access patterns for multi-team data environments
Enable experimentation and data development with reliable tooling and automated data workflows

Position Overview
We are seeking an Intermediate Data Platform Engineer to help build and scale a modern data ecosystem. In this role, you’ll contribute to distributed data systems, ETL/streaming pipelines, metadata platforms, and frameworks that support experimentation across the organization.
You will develop platform features, enhance observability, ensure data reliability, and collaborate with engineering and data science teams to support new initiatives.

Key Responsibilities
Data Platform Engineering
Build and maintain scalable data storage, transformation, and processing systems
Support Iceberg-based data lakehouse architecture and metadata catalogs
Develop ETL and streaming pipelines using Spark, Kafka, Parquet, and Iceberg
Build backend services in Python, Go, Scala, or Java to enhance platform capabilities
Contribute to Trino query performance and metadata optimization
Experimentation & Analytics Enablement
Develop tooling that improves experiment design, tracking, and analysis
Collaborate with data science and analytics teams to support experimentation workflows
Automate components of A/B testing and experimentation frameworks
Data Reliability, Security & Governance
Maintain and improve platform-level RBAC and AWS IAM configuration
Use Datadog for logging, alerting, and monitoring platform performance
Support schema evolution, data quality, and reproducibility across pipelines
Infrastructure & Deployment
Deploy and support services using Kubernetes and Helm
Improve automation, performance, and cost efficiency of data workloads
Contribute to capacity planning for data-intensive services
Collaboration & Documentation
Participate in cross-team engineering discussions
Document platform components to support internal stakeholders

Qualifications
Degree in Computer Science, Engineering, or related field
3+ years in data platform, data engineering, or platform engineering
Production-level coding experience in Python , Go , Scala , or Java
Experience supporting Iceberg-based data warehouses
Hands-on experience with Spark , Kafka , Trino , and distributed systems
Familiarity with RBAC systems, IAM, and data governance principles
Experience with Kubernetes, Helm, and CI/CD workflows
Strong troubleshooting and communication skills

Why Join Us
Join a team focused on building scalable, modern data infrastructure that powers experimentation and analytics. You’ll gain exposure to leading-edge tools and architectures while contributing to systems used across the organization.

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