Senior Data Engineer, LATAM

Fully remote for candidates based in Latin America.

Actively hiring, first seen by us 3 hours ago

Pay: USD 80,000–120,000/year · Base — pay source
Compensation & Benefits Base salary: $80,000 to $120,000 USD annually. Visa sponsorship is not available. Location
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Work setting: Remote — work setting source
Listed location: remote
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Employment: Full-time — employment source
Employment type in the employer’s posting: FullTime
From the employer’s posting

Before you apply

Work authorization: Must already have the right to workVisa sponsorship is not available

What you’ll work on

Join a data infrastructure and analytics team building a platform that turns information from multiple sources into reliable, current company intelligence.

You will own the platform end-to-end, from architecture and ingestion through production operations.
Design a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
Build intake pipelines for APIs, webhooks, files, and web scraping, with rate limits and robust failure handling.

From the employer’s posting

Join a data infrastructure and analytics team building a platform that turns information from multiple sources into reliable, current company intelligence. You will own the platform end-to-end, from architecture and ingestion through production operations.

About the Role Join a data infrastructure and analytics team building a platform that turns information from multiple sources into reliable, current company intelligence. You will own the platform end-to-end, from architecture and ingestion through production operations. What You'll Do

What You'll Do Design a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows. Build intake pipelines for APIs, webhooks, files, and web scraping, with rate limits and robust failure handling.

Design a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows. Build intake pipelines for APIs, webhooks, files, and web scraping, with rate limits and robust failure handling. Orchestrate scheduled workflows and historical backfills using tools such as Airflow, Dagster, or Prefect.

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Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Nov 11, 2026today
Recorded sightings: 1
Employer says posted: Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 55.

From 12,966 similar postings that came down. Coming down is not always a hire.

clera is hiring

16 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
dbt
PostgreSQL
Prefect
Airflow
Dagster
GCP
Google Cloud Storage

Where the posting names them

- Hands-on production experience with dbt and Google Cloud Platform, and workflow orchestration using Airflow, Dagster, Prefect, Temporal, or a comparable tool. Airflow is preferred. - Strong Python skills, including asynchronous HTTP and concurrent processing with asyncio, aiohttp, or HTTPX. - Strong SQL and PostgreSQL skills, including data modeling, query optimization, and reliable incremental loading.

- Strong Python skills, including asynchronous HTTP and concurrent processing with asyncio, aiohttp, or HTTPX. - Strong SQL and PostgreSQL skills, including data modeling, query optimization, and reliable incremental loading. - Experience building event-driven systems with messaging or task queues, asynchronous processing, and failure recovery.

- Develop messaging and task queue systems with retries, dead-letter queues, and controlled replay. - Preserve source payloads in Google Cloud Storage and transform data with dbt into raw, standardized, and curated layers. - Implement idempotent upserts, data contracts, automated validation, pipeline tests, and monitoring for freshness and failures.

- At least 5 years building and operating production data platforms across multiple sources, with ownership from architecture through deployment and ongoing operations. - Hands-on production experience with dbt and Google Cloud Platform, and workflow orchestration using Airflow, Dagster, Prefect, Temporal, or a comparable tool. Airflow is preferred. - Strong Python skills, including asynchronous HTTP and concurrent processing with asyncio, aiohttp, or HTTPX.

- Implement idempotent upserts, data contracts, automated validation, pipeline tests, and monitoring for freshness and failures. - Design and optimize PostgreSQL schemas and loading patterns, and integrate enrichment and LLM-based structured extraction. What We're Looking For

- Build intake pipelines for APIs, webhooks, files, and web scraping, with rate limits and robust failure handling. - Orchestrate scheduled workflows and historical backfills using tools such as Airflow, Dagster, or Prefect. - Develop messaging and task queue systems with retries, dead-letter queues, and controlled replay.

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

About the Role

Join a data infrastructure and analytics team building a platform that turns information from multiple sources into reliable, current company intelligence. You will own the platform end-to-end, from architecture and ingestion through production operations.

What You'll Do

Design a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
Build intake pipelines for APIs, webhooks, files, and web scraping, with rate limits and robust failure handling.
Orchestrate scheduled workflows and historical backfills using tools such as Airflow, Dagster, or Prefect.
Develop messaging and task queue systems with retries, dead-letter queues, and controlled replay.
Preserve source payloads in Google Cloud Storage and transform data with dbt into raw, standardized, and curated layers.
Implement idempotent upserts, data contracts, automated validation, pipeline tests, and monitoring for freshness and failures.
Design and optimize PostgreSQL schemas and loading patterns, and integrate enrichment and LLM-based structured extraction.

What We're Looking For

At least 5 years building and operating production data platforms across multiple sources, with ownership from architecture through deployment and ongoing operations.
Hands-on production experience with dbt and Google Cloud Platform, and workflow orchestration using Airflow, Dagster, Prefect, Temporal, or a comparable tool. Airflow is preferred.
Strong Python skills, including asynchronous HTTP and concurrent processing with asyncio, aiohttp, or HTTPX.
Strong SQL and PostgreSQL skills, including data modeling, query optimization, and reliable incremental loading.
Experience building event-driven systems with messaging or task queues, asynchronous processing, and failure recovery.
Experience with data contracts, raw and curated storage, retention policies, automated testing, and production monitoring.
Helpful experience includes web scraping, entity resolution, company and people data enrichment, LLM-based extraction, and building platforms from scratch in small teams.

Compensation & Benefits

Base salary: $80,000 to $120,000 USD annually. Visa sponsorship is not available.

Location