Senior Data Engineer — Remote LATAM, End-to-End Pipelines

Hidden Jobs; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

100% remote LATAM

Full-time B2B contract

High ownership & autonomy

Direct impact on architecture

Small international team

Job summary

onhires is seeking a senior, hands-on data engineer to join a small international team on a fully remote LATAM contract. You will own end-to-end data production from design to delivery across large-scale processing, standardization, matching, and quality.

The role emphasizes autonomy, strong Python and Spark skills, data modeling, and building robust ETL/ELT pipelines on modern data platforms, with meaningful impact on architecture and product direction.

Qualifications

• 4+ years of hands-on data engineering experience with production data systems.
• Strong Python skills and experience with PySpark or Apache Spark.
• Proven ability to build and maintain ETL/ELT pipelines and data ingestion.
• Solid SQL and data modelling skills; experience with data lakes or lakehouse.
• Ability to work independently, troubleshoot production issues, and own delivery.
• Fluent English.

Responsibilities

• Design, build, and maintain scalable production data pipelines.
• Ingest, process, and transform large volumes of data from multiple sources.
• Develop solutions for data standardization, normalization, matching, and validation.
• Build data quality controls and monitoring to catch malformed data.
• Take end-to-end ownership of technical solutions and production quality with a small team.

Skills

Python

PySpark / Apache Spark

SQL

ETL/ELT pipelines

Data modeling

Data quality & monitoring

English fluency

Independent / self‑driven

Tools

Databricks

Docker

Linux

Job description

onhires is seeking a senior, hands-on data engineer to join a small international team on a fully remote LATAM contract. You will own end-to-end data production from design to delivery across large-scale processing, standardization, matching, and quality.

The role emphasizes autonomy, strong Python and Spark skills, data modeling, and building robust ETL/ELT pipelines on modern data platforms, with meaningful impact on architecture and product direction.