Pay
In line with similar jobs
$120K–$160K against $127K–$190K, the middle half of what similar US postings state.
From 2,229 postings in the last year. Stated ranges, not salaries paid.
Senior Data Engineer
Remote within the United States. New York-based candidates are welcome, but New York residence is not required.
Actively hiring, first seen by us 3 hours ago- Pay
$120,000–160,000/year · Base — pay source
Compensation & Benefits Base salary: $120,000 to $160,000 annually. Visa sponsorship is not available. Location
Read the full posting- Work setting
Remote — work setting source
Listed location: remote
Read the full posting- 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 work
Visa sponsorship is not available
What you’ll work on
Full postingJoin 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.
Design and build a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
Build event-driven systems with messaging or task queues, including retries, dead-letter queues, and controlled replay.
From the employer’s posting
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.
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
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.
Posting record
Report an errorActively 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 recordSee 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
- BigQuery
- dbt
- PostgreSQL
- Prefect
- Airflow
- Dagster
- GCP
- Google Cloud Storage
Where the posting names them
- 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.
- 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
- 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.
- 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.
- 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
- 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.
- 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.
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
Applying through Ashby
- No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.
Already applied? Track this application
Has clera posted this job before?
Yes. We’ve followed one other Senior Data Engineer job there since November 2026. It is still up.
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.
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
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Compensation & Benefits Base salary: $120,000 to $160,000 annually. Visa sponsorship is not available. Location
- Location & working pattern
remote
Location Remote within the United States. New York-based candidates are welcome, but New York residence is not required.
- Work authorization
Compensation & Benefits Base salary: $120,000 to $160,000 annually. Visa sponsorship is not available. Location