# Senior Data Engineer at Clera

Senior Data Engineer at Clera in remote. Remote, full-time, paying $120k–$160k. Posted November 5, 2026.

- Company: Clera
- Location: remote
- Workplace: Remote
- Job type: Full-time
- Pay: $120k–$160k
- Posted: 2026-11-05
- Apply: https://jobs.ashbyhq.com/clera/a78f4d82-262e-4f05-bbd3-86cb2132fb98/application
- Source: https://jobmagic.ai/jobs/senior-data-engineer-clera-q57j13

## Requirements

- At least 5 years building and operating production data platforms across multiple sources, from architecture through ongoing operations.
- Production experience with workflow orchestration, including dependencies, retries, and failure recovery. Airflow is preferred; Dagster, Prefect, Temporal, or comparable tools are relevant.
- Hands-on production experience with dbt and Google Cloud Platform.
- Strong Python skills, including asynchronous HTTP and concurrent processing with asyncio, aiohttp, HTTPX, or similar tools.
- 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 recovery from failures.
- Experience implementing data contracts, raw and curated storage, retention policies, automated validation, pipeline tests, and monitoring.
- Web scraping, entity resolution, data enrichment, BigQuery, or Dataform experience is helpful, as is building platforms from scratch in a small team.

## Description

### About the Role

Join a data infrastructure and analytics team building a platform that turns information from many 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 and build a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.

- Ingest data from provider APIs, webhooks, files, and web scraping, with rate limiting and robust failure handling.

- Orchestrate scheduled workflows and historical backfills using Airflow, Dagster, Prefect, or similar tools.

- Build event-driven systems with messaging or task queues, including retries, dead-letter queues, and controlled replay.

- Preserve original payloads in Google Cloud Storage and transform them with dbt into raw, standardized, and curated layers.

- Implement idempotent upserts and safe retries to prevent duplicate records and data corruption.

- Define 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, from architecture through ongoing operations.

- Production experience with workflow orchestration, including dependencies, retries, and failure recovery. Airflow is preferred; Dagster, Prefect, Temporal, or comparable tools are relevant.

- Hands-on production experience with dbt and Google Cloud Platform.

- Strong Python skills, including asynchronous HTTP and concurrent processing with asyncio, aiohttp, HTTPX, or similar tools.

- 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 recovery from failures.

- Experience implementing data contracts, raw and curated storage, retention policies, automated validation, pipeline tests, and monitoring.

- Web scraping, entity resolution, data enrichment, BigQuery, or Dataform experience is helpful, as is building platforms from scratch in a small team.

### Compensation & Benefits

Base salary: $120,000 to $160,000 annually. Visa sponsorship is not available.

### Location

Remote within the United States. New York-based candidates are welcome, but New York residence is not required.