Senior Data Engineer

Clera
Laos
Remote

Who this role is best for

Data platform architects with 5+ years of full-stack data engineering experience will find this remote role at a Latin America-based company emphasizing end-to-end ownership and cloud infrastructure.

Best fit for

  • Candidates with 5+ years of full-stack data platform ownership and GCP/dbt expertise
    — “At least 5 years building and operating production data platforms, with ownership from architecture through deployment and ongoing operations.”
  • Individuals skilled in asynchronous Python and event-driven systems for scalable data pipelines
    — “Strong Python skills, including asynchronous HTTP and concurrent processing with asyncio, aiohttp, or HTTPX.”
  • Professionals experienced in designing data contracts and ensuring data quality across layers
    — “Experience with data contracts, raw and curated storage, retention policies, automated testing, and data quality monitoring.”

Things to consider

  • Remote work is required, with a base in Latin America, which may affect time zone alignment
    — “Remote, based in Latin America.”
  • No visa sponsorship available, which may limit eligibility for non-Latin American candidates
    — “Visa sponsorship is not available.”

How to stand out

  • Highlight end-to-end platform ownership in your resume and interview examples
    — “You will own the platform end-to-end, from architecture and ingestion to production operations”
  • Quantify experience with workflow orchestration tools like Airflow or Prefect
    — “Orchestrate scheduled workflows and historical backfills using tools such as Airflow, Dagster, or Prefect.”
  • Demonstrate expertise in PostgreSQL schema design and incremental loading techniques
    — “Design and optimize PostgreSQL schemas and loading patterns, and integrate enrichment and LLM-based structured extraction.”
  • Showcase robust failure handling and retry mechanisms in data ingestion pipelines
    — “Ingest data from APIs, webhooks, files, and web scraping, with rate limits and robust failure handling.”
  • Emphasize experience with data validation and pipeline monitoring practices
    — “Implement idempotent upserts, data contracts, automated validation, pipeline tests, and monitoring for freshness and failures.”
Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Design and build a multi-source data platform
Typical background
5+ years of experience in building and operating production data platforms

Skills & requirements

Required

Data Platform DesignCloud Data StorageData IngestionEvent-driven SystemsWorkflow OrchestrationSQLPostgreSQLPythonAsyncioAiohttpHttpxdbtAirflowDagsterPrefectTemporal

Preferred

Web ScrapingEntity ResolutionData EnrichmentLlm-based Extraction

Stack & domain

PythonGoogle Cloud PlatformdbtAirflowDagsterPrefectTemporalPostgreSQLAsyncioAiohttpHttpxSQLEvent-driven SystemsMessaging Or Task QueuesAsynchronous ProcessingFailure RecoveryData ContractsRaw And Curated StorageRetention PoliciesAutomated TestingData Quality Monitoring

About the role

Original posting from Clera via Ashby

ABOUT THE ROLE

Join a data and infrastructure team building a platform that turns information from multiple sources into reliable, up-to-date company intelligence. You will own the platform end-to-end, from architecture and ingestion to production operations, helping provide trusted data for downstream products.

WHAT YOU'LL DO

  • Design and build a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
  • Ingest data from 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.
  • Build messaging and task queue workflows with retries, dead-letter queues, and controlled replay.
  • Store original payloads in cloud object 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, with ownership from architecture through deployment and ongoing operations.
  • Production experience with Google Cloud Platform, dbt, and workflow orchestration tools such as Airflow, Dagster, Prefect, or Temporal.
  • 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 incremental loading.
  • Experience with event-driven systems, messaging or task queues, asynchronous processing, and failure recovery.
  • Experience with data contracts, raw and curated storage, retention policies, automated testing, and data quality monitoring.
  • Startup or small-team experience is valuable. Web scraping, entity resolution, data enrichment, and LLM-based extraction are also useful.

COMPENSATION & BENEFITS

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

LOCATION

Remote, based in Latin America.

Source: Clera careers (Ashby)

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