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Posted 14 days ago
Requirements and responsibilities
About the role:
We are looking for a Senior Data Engineer to join our partner companies building modern data infrastructure for AI-native U.S. startups. You will design and build the data pipelines, warehouses, and analytics layer that power business intelligence and machine learning workflows. Work for innovative companies that treat data as a first-class product surface.
Responsibilities:
- Design and build scalable ETL/ELT pipelines using modern tools (Airflow, dbt, Dagster).
- Architect data warehouses on Snowflake, BigQuery, or Redshift.
- Build data models for analytics, ML features, and product dashboards.
- Implement data quality, observability, and lineage tooling.
- Optimize query performance and warehouse costs.
- Collaborate with analytics and ML teams on data contracts and schema design.
Requirements:
- 5+ years of professional data engineering experience.
- Strong Python and advanced SQL skills (query optimization, window functions, CTEs).
- 3+ years with modern data warehouses (Snowflake, BigQuery, or Redshift).
- Hands-on experience with dbt and orchestration tools (Airflow, Dagster, or Prefect).
- Familiarity with both streaming (Kafka, Kinesis) and batch processing patterns.
- Excellent English communication skills (B2+).
Nice to have:
- Experience with Spark, Databricks, or similar big-data frameworks.
- Knowledge of feature stores (Feast, Tecton) for ML pipelines.
- Background with data observability tools (Monte Carlo, Great Expectations).
- Experience designing event tracking schemas and product analytics pipelines.
Tech stack:
- Python.
- SQL.
- dbt.
- Airflow.
- Snowflake.
- BigQuery.
- AWS.
Benefits:
- Competitive USD salary.
- 100% remote work.
- Flexible working hours.
- Professional development budget.
- Health insurance stipend.
- Equipment allowance.
Location:
- Remote (LATAM) — open to candidates across Latin America.
Optionally, you can add more information later (benefits, pre-screening questions, etc.)