What will I be doing?

• Own, operate, and optimize DynamoDB workloads in production, including data modeling, capacity strategy (provisioned/on‑demand), GSIs/LSIs, TTL, Streams, backup/restore, and multi‑region patterns.

• Design, deploy, and maintain relational and not relational databases, including sharding, indexing strategies, backups, and performance tuning.

• Leverage AWS services across the data stack (e.g., S3, KMS, IAM, CloudWatch, DMS, Lambda) to build reliable, observable, and secure data solutions.

• Implement automation-as-code (CLI/SDK) for schema and capacity changes, operational tasks, and guardrails to reduce toil and error.

• Establish and improve observability for databases (metrics, logs, traces, dashboards, SLOs/alerts) and lead performance/root‑cause investigations.

• Collaborate with engineers to design efficient data access patterns and guide migrations and schema evolution with minimal downtime.

• Contribute to reliability engineering practices (backups, DR, chaos/restore testing, incident reviews) across NoSQL platforms.

• Participate in an on‑call rotation and attend emergency escalations, including during off‑hours when required

What skills do I need?

At dLocal, we embrace an AI‑first culture—using AI tools is a standard part of how we design, build, and operate.

Hands‑on, senior‑level expertise operating DynamoDB in production (table design and single‑table modeling, indexes, Streams, backup/restore, performance/cost optimization) — this is a must‑have.

Experience with AWS MSK or Kafka for event‑driven and streaming use cases — highly valued.

Experience with DocumentDB and/or MongoDB administration (cluster sizing, replication/sharding, indexing, backups, upgrades, performance tuning).

Solid command of AWS cloud fundamentals for data platforms (IAM, KMS encryption, networking basics, S3 patterns, monitoring/alerting with CloudWatch; experience with DMS and Lambda is a plus).

Automation proficiency using Python or JavaScript/TypeScript, GO the AWS CLI, and SDKs to build repeatable operations and safety checks.

Working knowledge of relational databases as a plus (e.g., MySQL/Aurora, PostgreSQL) to partner with peers and support hybrid data designs.

Clear communication in English and a collaborative, service‑oriented mindset working with distributed teams.

Nice to Have

Certifications in AWS (e.g., Solutions Architect, Database – Specialty) or equivalent demonstrable expertise.

Experience with infrastructure as code and Git‑based workflows (e.g., Terraform/CloudFormation, GitOps).

Exposure to containers/orchestration (ECS/EKS) and securing data workloads in cloud‑native environments.

Prior work with DocumentDB/MongoDB performance tuning at scale and multi‑region topologies.

Ownership and bias for action, with strong troubleshooting instincts and attention to detail.

Proactive approach to automation, continuous improvement, and reliability engineering.

Collaboration and communication that builds trust across engineering, platform, and operations teams.