Senior Data Engineer

🕒 Setembro 17

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $135.000 - $165.000 / ano

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

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Worldly

SiteLinkedInTodas as Vagas

51 - 200 funcionários

💼 Consultoria

🏭 Manufatura

📦 Logística

Consulting • Manufacturing • Logistics

A Worldly é uma fornecedora líder de soluções de inteligência em sustentabilidade para marcas e fabricantes. A empresa ajuda negócios a desenvolver e escalar programas de sustentabilidade ao entregar dados reais sobre suas cadeias de suprimentos, produtos e operações. A plataforma da Worldly inclui ferramentas para monitorar impactos de fábricas, assegurar compliance regulatório e entender os impactos de produtos por meio de frameworks padronizados como o Higg Index. Seus serviços apoiam avaliações de desempenho ambiental e social, relatórios ESG e transparência na cadeia de suprimentos. Os clientes da Worldly se beneficiam de maior visibilidade sobre suas cadeias de suprimentos e de insights acionáveis para aprimorar seu desempenho em sustentabilidade e cumprir novas regulamentações.

Descrição

• Build, operate, maintain, and evolve systems supporting internal analytics and customer-facing analytics platforms • Own the production CDC-fed medallion data lake on Apache Iceberg queried through Trino • Operate and evolve the Postgres data warehouse, including schema, performance, access controls, and analytics-ready datasets • Own CDC ingestion from source databases through message bus, streaming writer, and Iceberg bronze/silver/gold layers • Operate the Trino query layer and table catalog • Own pipeline health, including latency SLAs, schema-drift detection, and source reconciliation • Manage GitOps/Terraform infrastructure and backup/disaster-recovery posture • Establish consistent schemas, documented lineage, and clear ownership across the data estate • Maintain and evolve Dagster-orchestrated dbt pipelines, including sensor-triggered and scheduled builds, data-quality tests, and branch-based versioning • Operate the BI/reporting layer with per-user, policy-based data access and consistent metric definitions • Own pipelines integrating the graph database with the warehouse, lake, and primary databases • Migrate legacy direct-to-graph services onto a shared integration path and evolve relational structures into graph-native models • Support and extend production genAI workflows including embeddings/similarity search and LLM-based extraction and classification • Keep data infrastructure AI-ready • Collaborate with data science and cross-functional analytics stakeholders • Participate in incident triage, root-cause analysis, runbook development, and reliability improvements

🎯 Requisitos

• 5+ years in data engineering, analytics engineering, or data platform engineering • Advanced SQL and relational database experience with Postgres and MongoDB • Hands-on graph database experience in production, including integration with warehouses and lakes • Experience with open table formats and medallion lake architectures such as Apache Iceberg • Experience with distributed SQL engines such as Trino or Presto • Experience with streaming/CDC pipelines such as Kafka or Pulsar, Debezium, and Flink or similar • Strong Python skills for pipelines, automation, and operational tooling • Experience with dbt orchestrated by a modern scheduler such as Dagster or Airflow • AWS infrastructure experience with EKS, VPC, IAM, and S3 via infrastructure-as-code such as Terraform • Experience with CI/CD, GitOps such as ArgoCD, and Docker • Experience with analytics data modeling, metric definitions, and automated monitoring/data-quality controls • Experience operating production data systems, including incident triage, root-cause analysis, runbooks, and reliability improvements • Comfortable working with cross-functional/analytics stakeholders using Jira/Confluence and Agile • Familiarity with data security practices including PII protection, encryption, and access management • Experience with BI tooling supporting per-user, policy-based data access is helpful • Experience with policy-based access control and identity platforms is helpful • Familiarity with multi-region data residency is helpful • Must be located in and legally eligible to work in the United States • Must have 5+ years of hands-on experience in data engineering, analytics engineering, or data platform engineering • Must have worked with graph databases in production and integrated them with data warehouses or data lakes • Must have direct experience building and maintaining data pipelines using streaming/CDC technologies

🏖️ Benefícios

• Medical, Dental, and Vision Insurance through multiple PPO options; employer covers 90% of employee premiums and 60% of spouse/dependent premiums • Company-sponsored 401k with up to 4% match for US employees • Incentive Stock Options • 100% Parental Paid Leave • Unlimited PTO • 12 paid company holidays • Performance-based bonuses • Office stipend • No-meeting Fridays • Flexible time off • Culture committee, coffee chats, and interest groups • Work-from-home stipends • Occasional travel for business needs