Data Engineers
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 21d ago
The date the source published, not the day we noticed it (2026-09-21). Last seen at its source 3h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Not stated
The description states no restriction of its own. This is the source's own tag.
Pay
$17/hr
Published by the source in its own salary field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
BambooHR employer's own board first seen 3h ago · last seen 3h ago
The listing
Data Engineer
Job Overview
We are looking for a skilled Data Engineer to design, optimize, and maintain the data architecture that powers our BI environment.
This role focuses on building scalable BigQuery datamarts, optimizing data models, and ensuring reliable data pipelines to support analytics and reporting.
The ideal candidate has strong experience in cloud data warehousing, data modeling, and building analytics-ready datasets that enable efficient BI consumption.
Key Responsibilities
1. Data Architecture & Engineering
- Design, build, and maintain BigQuery datamarts and analytical tables for BI reporting.
- Develop scalable data models, including star schema, snowflake, and denormalized models.
- Optimize query performance and storage efficiency within cloud data warehouses.
- Collaborate with BI teams to ensure datasets align with semantic models and dashboards.
2. Data Pipeline & Transformation
- Build and maintain data pipelines for data ingestion, transformation, and loading into analytics environments.
- Implement transformation workflows using SQL or frameworks such as dbt.
- Ensure data quality, validation, and consistency across datasets.
3. Data Governance & Performance
- Maintain data standards, naming conventions, and proper documentation.
- Implement governance practices, including schema management and version control.
- Monitor and troubleshoot pipeline failures and data inconsistencies.
4. Collaboration with BI Teams
- Work closely with BI specialists to ensure datasets support semantic-layer requirements.
- Deliver optimized datasets that minimize the need for heavy transformations within BI tools.
Required Qualifications
- 3+ years of experience in Data Engineering or Analytics Engineering.
- Strong SQL expertise for analytical workloads.
- Experience with cloud data warehouses such as:
- BigQuery
- Amazon Redshift
- Snowflake
- Similar platforms
- Proven experience designing star-schema or dimensional data models.
- Experience building analytics-ready datamarts.
Preferred Qualifications
- Experience with dbt or similar data-transformation frameworks.
- Familiarity with Git-based workflows and CI/CD for data pipelines.
- Experience with BI tools such as:
- Looker
- Tableau
- Power BI
- Background working with retail or multi-location data environments.
Key Skills
- SQL
- Prompt Engineering
- Data Engineering
- Analytics Engineering
- BigQuery
- Data Modeling
- Data Warehousing
- Data Pipelines
- BI & Analytics
- dbt
- Git / CI/CD