Database Engineer

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Solvd, Inc.

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501 - 1000 funcionários

Fundada em 2010

💼 Consultoria

🏥 Saúde

📦 Logística

Consulting • Healthcare • Logistics

Solvd, Inc. é uma empresa global de engenharia de software e consultoria que entrega soluções completas end-to-end. Fundada em 2011, a Solvd oferece serviços centrais de engenharia, incluindo desenvolvimento de software para plataformas web e mobile, experiência digital e design, soluções de Data e AI/ML e modernização de plataformas em cloud. A empresa é parceira da AWS e é reconhecida por otimizar recursos, resolver problemas complexos e elevar a satisfação dos usuários. A Solvd enfatiza inovação e Quality Assurance (QA), empregando mais de 800 profissionais internacionais em 8 escritórios pelo mundo. A empresa se orgulha de transformar negócios ao fornecer produtos digitais ricos em funcionalidades, testes manuais, automação e soluções tecnológicas de ponta. Suas ferramentas proprietárias, como Zebrunner e Carina, ajudam a aprimorar os processos de desenvolvimento e QA. A Solvd opera com foco em colaboração, atração e desenvolvimento de talentos de alto nível e soluções técnicas personalizadas às necessidades de cada cliente, atendendo clientes em 15 países.

Descrição

• Implement and operate cross-region replication for one or more of: Aurora MySQL Global Database, DynamoDB Global Tables, DocumentDB Global Clusters, Cassandra multi-DC topology, ElastiCache / MemoryDB / Valkey global datastore, Neptune Global Database, OpenSearch cross-cluster replication. • Codify everything in Terraform (or CDK). • Build the observability layer for replication health: lag metrics, consistency checks, alarm thresholds, and runbook automation. Datadog is the primary observability stack; CloudWatch is the baseline. • Author and execute failover and failback runbooks. Run game-days using AWS Fault Injection Service. Measure and report against RTO and RPO targets. • Implement KMS cross-account replication, IAM service principals for replication roles, and the secrets and parameter strategy for region-local dependencies. • Support data extraction from the monolith into microservices: build CDC pipelines (DMS, DynamoDB Streams, Kafka Connect, Debezium), validate data integrity, and own the cutover sequence for individual extractions. • Pair with application engineers on connection-string abstraction, retry and idempotency patterns, and graceful degradation during region failover. • Write design docs and runbooks the client team can take over after the engagement.

🎯 Requisitos

• 5+ years in production database engineering on AWS, with hands-on responsibility for at least one of: payments, banking, brokerage, or comparable financial-services workloads. • Deep production experience with at least two of: Aurora MySQL, Cassandra, DynamoDB, ElastiCache (Redis or Valkey), DocumentDB, Neptune. Working knowledge of at least two more. • Practical experience with cross-region replication in production: you've configured Global Database, Global Tables, multi-DC Cassandra, or equivalent, and you've handled the failure modes (replication lag spikes, split-brain risk, version-skew issues). • Strong Terraform (or CDK). You can build a multi-region module from scratch and explain the trade-offs. • Comfort with CDC tooling (DMS, DDB Streams, Kafka Connect, or Debezium) and the operational gotchas (schema drift, ordering guarantees, replay). • Linux, networking fundamentals (VPC, Transit Gateway, peering, DNS), and IAM / KMS proficiency. • Solid written communication and ability to operate in a regulated client environment. • Cassandra multi-DC operations experience at scale (nodetool workflows, repair strategy, tombstone management, cross-region anti-entropy). • AWS MSK or Kafka MirrorMaker 2 experience for cross-region event replication. • Experience with Datadog Database Monitoring and custom CloudWatch metrics. • AWS Database Specialty or Solutions Architect Associate / Professional certifications.

🏖️ Benefícios

• Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. • Be part of a global team with equal opportunities for collaboration across continents and cultures. • Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards.