Senior Data Engineer

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

This is a senior, hands‑on data engineering role on a small international team at a market intelligence and software company. The work centers on large-scale data processing, standardization, matching, and data quality, with end‑to‑end ownership from design through reliable production delivery. The position is fully remote across Latin America on a full‑time B2B contract.

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 or inconsistent data
• Design reliable approaches to corrections, updates, reprocessing, and backfills
• Improve the architecture, scalability, reliability, and performance of the data platform
• Take end‑to‑end ownership of technical solutions and production quality while working with a small engineering team

Requirements

• 4+ years of hands‑on data engineering experience with production data systems
• Strong Python skills
• Hands‑on experience with PySpark or Apache Spark for distributed data processing
• Strong experience building and maintaining ETL/ELT and ingestion pipelines
• Solid SQL and data modelling skills
• Experience with modern data platforms, data lakes, or lakehouse architectures
• Strong understanding of data quality, validation, monitoring, and reliability
• Ability to work independently, troubleshoot production issues, and own delivery
• Fluent English

Nice to have

• Delta Lake, MongoDB, or Databricks experience
• Background in data matching, reconciliation, deduplication, or complex standardisation
• Experience in start‑ups, scale‑ups, or small product engineering teams
• Docker, Linux, CI/CD, or related DevOps exposure
• Experience mentoring other engineers while remaining hands‑on
• Active use of AI coding or agent‑based development tools

Benefits and work setup

• 100% remote from LATAM
• Full‑time B2B contract
• High level of technical ownership and autonomy
• Direct impact on architecture and product development
• Complex engineering challenges rather than narrowly scoped implementation work
• Small international team with minimal bureaucracy and direct communication