Data Engineer

This is a fully remote position, open to applicants in Argentina, +5 more countries.

📋 Description

• Develop batch and streaming ingestion and transformation pipelines utilizing Spark, Kafka, dbt, and Airflow.

• Strategically address idempotency, backfills, schema evolution, and late-arriving data.

• Design data warehouses and lakehouses on platforms such as Snowflake, BigQuery, Redshift, or Databricks.

• Take ownership of partitioning, file layout, query cost, and performance considerations.

• Construct chunking, embedding, and indexing pipelines for RAG retrieval systems.

• Manage retrieval infrastructure using pgvector, Pinecone, Qdrant, or Azure AI Search.

• Set up data quality tests, expectations, lineage, and alert notifications.

• Implement PII classification, masking, and manage row- and column-level access, retention, deletion, and audit trails.

• Deploy and maintain containerized systems on Azure or AWS.

• Oversee CI/CD, orchestration, observability, cost management, and runtime budgets.

• Engage within client environments, repositories, standups, and occasionally participate in customer calls.

• Utilize AI-assisted development tools and automated codebase audits to uphold security, cost efficiency, and architectural integrity.

• Collaborate with client teams in alignment with their working hours.

⛳️ Requirements

• A minimum of 5 years of experience in building and operating production data pipelines.

• Proficiency in Python and SQL as primary programming languages.

• Experience in testing, code review, CI/CD, Git, containers, and orchestration.

• Strong expertise in designing and constructing data warehouses or lakehouses.

• Knowledge of dimensional modeling and incremental processing.

• Familiarity with distributed processing at production scale using Spark, Kafka, Flink, or similar technologies.

• Experience with production orchestration tools like Airflow, Dagster, or Prefect.

• Understanding of retries, idempotency, and backfill strategies.

• Ability to manage version-controlled transformations with tests and lineage using dbt or an equivalent tool.

• Experience with cloud deployment, preferably Azure, with AWS being acceptable.

• Proficiency with Docker, CI/CD pipelines, and infrastructure as code using GitHub Actions, Terraform, or Bicep.

• Capability to articulate pipeline cost, runtime, and throughput decisions.

• Active utilization of AI-assisted coding tools such as Claude Code, Cursor, or GitHub Copilot in project delivery.

• Excellent written and spoken English skills at C1 level or above.

• Confidence in explaining technical trade-offs directly to clients.

• A Bachelor's degree in Computer Science, Data Science, or a related field, or equivalent professional experience.

🏝️ Benefits

• Paid time off (PTO).

• Observance of U.S. Holidays.

• AI Training opportunities.

• Mentored career development programs.

• Profit-sharing initiatives.

• Competitive remuneration in USD.