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Senior Data Engineer

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This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer based in Brazil.

This is a senior-level opportunity to design and build the data infrastructure powering modern BI, AI, and LLM-driven applications.
You will take ownership of scalable end-to-end data pipelines, from ingestion and transformation to analytics, model training, and real-time inference.
The role combines traditional data engineering with emerging technologies such as vector databases, RAG, prompt engineering, and intelligent orchestration.
You will work closely with BI and data stakeholders to translate business and technical requirements into reliable, scalable solutions.
Your work will help enable natural-language analytics, AI-backed insights, advanced search, and data-driven decision-making.
The environment encourages continuous learning across data engineering, MLOps, and LLM operations.
This is a fully remote role for professionals based in Latin America, with long-term growth opportunities and a strong focus on technical development.

Accountabilities:

  • Design, develop, and maintain scalable data pipelines for data ingestion, transformation, and delivery into centralized feature stores, model-training workflows, and real-time inference services.
  • Build and optimize processes for extracting, storing, indexing, and retrieving semantic representations of unstructured data to support advanced search and retrieval use cases.
  • Develop lightweight analytics and dashboarding solutions that enable natural-language querying and AI-powered business insights.
  • Define and manage prompt engineering techniques, orchestration workflows, and model fine-tuning processes supporting conversational and LLM-powered applications.
  • Oversee vector data stores and implement efficient indexing strategies for retrieval-augmented generation (RAG) workflows.
  • Collaborate with BI and data stakeholders to gather requirements for language-model initiatives and translate them into scalable technical solutions.
  • Create and maintain comprehensive documentation covering data processes, workflows, pipelines, and model deployment routines.
  • Stay current with emerging methodologies, technologies, and best practices across data engineering, MLOps, and LLM operations.
  • Requirements:

    • 8+ years of professional experience in data engineering.
    • Strong Python skills for data engineering, transformation, advanced data manipulation, and large-scale processing.
    • Hands-on experience with big data technologies such as Apache Spark, Hadoop, and Kafka for distributed processing and real-time data ingestion.
    • Proven experience designing complex data pipelines using data from RDBMS, JSON, APIs, and flat-file sources.
    • Advanced SQL and PL/SQL skills, combined with strong knowledge of Business Intelligence and data warehouse methodologies.
    • Hands-on experience with relational databases and cloud-based database services such as Snowflake or Amazon Redshift.
    • Understanding of software engineering principles and experience working across Unix, Linux, and Windows environments.
    • Familiarity with Agile development methodologies and version control systems, including repository management, branching, merging, and collaborative development.
    • Strong interest in business operations and an understanding of how robust BI systems support profitability, data-driven decision-making, and strategic insights.
    • Excellent written and verbal English communication skills for collaboration with BI teams and business users.
    • Experience with vector databases such as DataStax AstraDB is a plus.
    • Experience developing LLM-powered applications using frameworks such as LangChain or LlamaIndex, including prompt engineering, RAG, and intelligent workflow orchestration, is desirable.
    • Familiarity with open-source LLM frameworks such as Hugging Face Transformers or LLaMA-4, including fine-tuning and inference optimization, is a plus.
    • Knowledge of MLOps tools and CI/CD pipelines for model versioning and automated deployments is desirable.
    • Benefits:

      • Fully remote work opportunity.
      • B2B employment with gross USD compensation.
      • Stable, long-term opportunity with strong growth potential.
      • High-quality professional hardware.
      • Learning and professional development opportunities.
      • Financial support for professional training, seminars, and conferences.
      • Employee referral program with rewards for successful referrals.
      • Company-supported English language classes.
      • Opportunity to work with talented professionals in a collaborative international environment.
      • Applicants must be based in Latin America, and in-person identity verification is required.
      • CV and interview process conducted in English.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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