Data Engineer

🕒 September 23

🌐 Argentina, Brazil, +4 more countries – Remote

🇦🇷 Argentina – Remote 🇧🇷 Brazil – Remote 🇨🇴 Colombia – Remote 🇲🇽 Mexico – Remote 🇨🇱 Chile – Remote 🇵🇪 Peru – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 11%

What it means: the chance that no one is really hiring for this job.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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Azumo

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Azumo is a leading software development company that specializes in nearshore services. The company offers a range of solutions, including software development, dedicated teams, staff augmentation, and virtual CTO services. Azumo is particularly known for its expertise in artificial intelligence, mobile app development, data engineering, and cloud services. The company prides itself on delivering high-quality, scalable, and innovative software solutions tailored to the specific needs of various industries, including fintech, game development, healthcare, and media. With a focus on assembling talented developers from Latin America, Azumo ensures time zone alignment and seamless communication with clients in North America. Their commitment to quality and client satisfaction is evidenced by numerous awards and positive client testimonials from prestigious organizations like Facebook, Twitter, and Discovery Channel.

📋 Description

• Build batch and streaming ingestion and transformation pipelines using Spark, Kafka, dbt, and Airflow • Handle idempotency, backfills, schema evolution, and late-arriving data by design • Design warehouses and lakehouses on Snowflake, BigQuery, Redshift, or Databricks • Own partitioning, file layout, query cost, and performance decisions • Build chunking, embedding, and indexing pipelines for RAG retrieval systems • Operate retrieval infrastructure using pgvector, Pinecone, Qdrant, or Azure AI Search • Establish data quality tests, expectations, lineage, and alerting • Implement PII classification, masking, row- and column-level access, retention, deletion, and audit trails • Deploy and operate containerized systems on Azure or AWS • Own CI/CD, orchestration, observability, cost, and runtime budgets • Work inside client environments, repositories, standups, and occasionally customer calls • Use AI-assisted development tools and automated codebase audits to maintain security, cost, and architecture quality • Collaborate with client teams aligned to their working day

🎯 Requirements

• 5+ years building and operating production data pipelines • Python and SQL as primary languages • Testing, code review, CI/CD, Git, containers, and orchestration • Expertise designing and building data warehouses or lakehouses • Dimensional modeling and incremental processing • Distributed processing at production scale with Spark, Kafka, Flink or equivalent • Production orchestration with Airflow, Dagster or Prefect • Retries, idempotency, and backfill strategy • Version-controlled transformation with tests and lineage using dbt or equivalent • Cloud deployment experience; Azure preferred and AWS acceptable • Docker, CI/CD pipelines, and infrastructure as code using GitHub Actions, Terraform, or Bicep • Ability to explain pipeline cost, runtime, and throughput decisions • Active use of AI-assisted coding tools such as Claude Code, Cursor, or GitHub Copilot in delivery work • Clear written and spoken English at C1 or above • Confidence explaining technical trade-offs directly to a client • Bachelor's degree in Computer Science, Data Science, or related field, or equivalent professional experience

🏖️ Benefits

• Paid time off (PTO) • U.S. Holidays • AI Training • Mentored career development • Profit sharing • $US remuneration

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