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Data Engineer

hace 2 semanas

Buenos Aires, Buenos Aires C.F., Argentina Consigliere Labs A tiempo completo

**This is a remote role open to candidates based in North, Central, and South America, as well as Europe.

We're seeking an experienced Data Engineer to develop robust data infrastructure across cloud ecosystems and work closely with AI engineers on data-driven AI applications.

You'll be laying the data foundations that power everything from analytics and performance feedback loops to LLM-powered content generation.

This role is ideal for someone who can architect modern data stacks with confidence, move quickly with autonomy, and collaborate closely with AI engineers, analysts, and product thinkers to make complex ideas work in the real world.

Work Location:
Remote first, must flex across EU and US hours - morning calls with EU and US meetings through 3PM PST. Must be based in North, Central, or South America, or Europe.

What we're building:

Consigliere is building an AI-powered set of tools for modern consumer brands. We combine expert creative strategy with automation to give teams a compounding edge: faster feedback loops, deeper insight, and smarter creative decisions. Our systems already support millions in monthly ad spend, now we're scaling them into production-ready tools.

Key Responsibilities:

  • Design, build, and maintain scalable ETL/ELT pipelines using Fivetran and dbt.
  • Drive the architectural vision to architect and optimize data storage solutions on AWS RDS, Redshift, and GCP BigQuery, making key decisions on data warehouse design, ETL strategies, data lake implementation, and real-time data processing.
  • Implement schema design, partitioning strategies, and cost‑efficient data architectures.
  • Collaborate with data analysts and AI engineers to define and deliver analytics and AI-ready data marts.
  • Ensure data quality and governance—monitoring, alerting, security, and compliance.
  • Orchestrate workflows using systems like Airflow, Prefect, or Dagster.
  • Facilitate reliable production pipelines supporting ML and Generative AI applications (e.g., vector databases, RAG workflows).
  • Design and implement scalable, reliable, and maintainable data architecture to support business intelligence, operational analytics, and data-driven product features.
  • Build and optimize data pipelines, define data models, and ensure data integrity across multiple sources and environments.

About you:

We're looking for an experienced data engineer who can move fast without sacrificing quality. Someone who knows how to balance immediate business needs with long-term data health. If you've felt boxed in by corporate red tape, this is the opposite: high agency, high impact, and lots of room to grow.

  • You're cracked—in a good way. You know how to build and ship fast.
  • You're not just a builder, you're a systems thinker. You see beyond tables and pipelines.
  • You're allergic to corporate BS. You prefer autonomy and ownership.
  • You know when to polish, and when done is better than perfect.
  • You love clean architectures and sharp schemas and can explain why.
  • You enjoy close collaboration with cross-functional teams and take ownership of your domain.
  • You're excited by the overlap of data infrastructure and AI workflows.
  • You have one year or more of experience incorporating AI into data engineering workflows.
  • Bonus: You've worked in startups, hacked on creative tools, or built products for marketers, designers, or writers.

Core Qualifications:

3–5 years of hands-on data engineering experience

  • Proven experience with Fivetran, dbt, RDS, Redshift, and BigQuery
  • Strong command of modern SQL (CTEs, window functions, performance tuning)
  • Proficiency in Python for ETL/ELT, orchestration, and monitoring

Solid understanding of data warehousing, modeling, and cloud best practices.

  • Comfortable working in hybrid cloud ecosystems and multi-tenant setups
  • Understand schema design, partitioning, data modeling, and cost optimization
  • Experience with workflow orchestration and pipeline monitoring.
  • Familiarity with data security, governance, and compliance (e.g., encryption, RBAC, GDPR).

Production-Ready Mindset

  • You care about SLAs, observability, and fail-safes. Not just getting things to work once
  • Familiar with DevOps, infra-as-code (Terraform, GitHub Actions), CI/CD best practices

Bonus points:

  • Cloud certifications (AWS, GCP)
  • DevOps/ Infrastructure-as-code / CI-CD experience (Terraform, GitHub Actions).
  • Experience in SaaS environments or with B2B/analytics-heavy products
  • A good eye for turning messy data into clean, structured assets for ML and insights
  • Hands-on experience with Generative AI / GenAI pipelines: familiarity with LLMs, retrieval-augmented generation (RAG), vector databases; ability to support AI engineers in productionizing GenAI models. This aligns with market trends where AI data engineers are expected to bridge traditional data pipelines with AI-specific needs, including unstructured and real-time data handling.

What we offer:

  • A front-row seat at a high-growth, profitable company building next-gen creative tools
  • Direct exposure to performance data from top-tier consumer brands
  • High agency, tight feedback loops, and the chance to influence architecture from day one
  • Competitive salary: $120,000–$150,000 USD based on experience + meaningful equity

We're building the infrastructure to support creative strategy at the speed of AI. If you're excited about connecting data systems to intelligent experiences, we'd love to talk.

Apply here:

Work Location:
Remote first, must flex across EU and US hours - morning calls with EU and US meetings through 3PM PST.