Intermediate Data Platform Engineer

Há 3 dias

São Paulo, 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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