Data Engineer

Job not on LinkedIn

🔥 2 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Escale

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

📣 Marketing

🤖 Artificial Intelligence

Consulting • Marketing • Artificial Intelligence

Escale is a Brazilian AI-driven sales technology company that builds and operates 'aisa', a multi-agent artificial intelligence salesperson trained on millions of real sales conversations. The platform automates lead qualification, objection handling, negotiation, and sale activation (including identity verification and payment/contract workflows), and is offered on a pay-for-success model to help companies increase digital sales conversion across industries. Escale positions itself as a replacement for traditional chatbots by delivering sales-focused AI agents and integrations for enterprise sales teams.

📋 Description

• Build, maintain, and evolve S3 → Databricks/Airflow → dbt pipelines • Scale the data platform to support the company’s growing data volumes • Monitor production pipelines and identify failures, delays, or anomalous data • Troubleshoot and adjust workflows when failures occur • Create metrics and monitor systems with a focus on operating costs, data quality, and consistency • Manage infrastructure as code using Terraform • Deploy the data platform through Kubernetes (EKS) and Argo • Ensure data governance through OpenMetadata, including availability, scalability, and access control • Identify PII and apply masking or anonymization before data is consumed for analytics or product use • Define and evolve self-service ELT/ETL tools • Prepare and deliver data for predictive models and LLMs, including RAG and embeddings where applicable • Evaluate new technologies and keep the production stack running reliably • Support internal teams that consume the platform by resolving technical questions and promoting best practices

🎯 Requirements

• Experience in software engineering (Python, Java, or Scala) and software development best practices (e.g., Clean Architecture and TDD) • Knowledge of Lambda data architecture and analytical data modeling • Experience with AWS, with ingestion centered on S3 • Experience with Databricks for distributed processing • Experience with Airflow for pipeline orchestration • Knowledge of Docker and Kubernetes, including stateless and stateful workloads • Experience with Terraform for infrastructure as code • Experience with Argo CD and declarative deployment through Kubernetes/EKS • Experience with dbt for analytical modeling and transformation • Experience with OpenMetadata for data governance, lineage, and access control • Familiarity with language model APIs, such as OpenAI, Cohere, and Hugging Face • Knowledge of security and sensitive data handling, including PII identification, masking, and anonymization • Experience with DataOps, monitoring, alerting, and troubleshooting failures in production pipelines • Kappa architecture as a complementary advantage to Lambda architecture • Knowledge of alternative open-source solutions for data ingestion, processing, and delivery • Understanding of data security and governance best practices, with DAMA as a conceptual reference • Interest in or familiarity with the fundamentals of LLMs and generative AI applied to data • Experience with streaming data processing technologies such as Kafka, Flink, and Druid