Time since we first saw it
Day 6
Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
Virtual, LKA
Actively hiring, first seen by us 6 days agoImplement per-user and per-location access in BigQuery with row-access policies and column masking
Design purpose-based access control (raw, anonymized, or aggregated) with policies enforced in BigQuery
Build an MCP service over the LookML semantic layer where AI agents inherit the user's access
Set guardrails on AI and ad-hoc query spend using quotas, bytes-billed limits, and slot reservations
Document security patterns and access procedures so the platform is easy to operate and review
Implement per-user and per-location access in BigQuery using row-access policies and column-level masking
Design and build purpose-based access control (raw, anonymized, or aggregated data depending on the declared purpose)
Build an MCP service over our LookML semantic layer.
Put guardrails on AI and ad-hoc query spend using custom quotas, maximum-bytes-billed limits, slot reservations, and caching.
Document security patterns and access procedures so the platform is easy to operate, review, and extend.
Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 6
Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
11 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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.
+ Strong SQL, plus enough familiarity with a semantic / BI layer (LookML or similar) to expose it safely. + Python or a comparable language for service development. + Comfort working on your own in a greenfield setting and setting patterns others follow.
+ Platform and integration engineering skills: you can build and run a service that handles authentication and passes user identity through to the data (OAuth or similar). + Strong SQL, plus enough familiarity with a semantic / BI layer (LookML or similar) to expose it safely. + Python or a comparable language for service development.
**What you'll do** + Enforce access in the data. Implement per-user and per-location access in BigQuery using row-access policies and column-level masking, so each person sees only the data they're entitled to. + Make purpose part of the policy. Design and build purpose-based access control (raw, anonymized, or aggregated data depending on the declared purpose), with policies authored in Collibra and enforced natively in BigQuery.
+ Enforce access in the data. Implement per-user and per-location access in BigQuery using row-access policies and column-level masking, so each person sees only the data they're entitled to. + Make purpose part of the policy. Design and build purpose-based access control (raw, anonymized, or aggregated data depending on the declared purpose), with policies authored in Collibra and enforced natively in BigQuery. + Open a governed door for AI. Build an MCP service over our LookML semantic layer. AI agents authenticate as the user and inherit that user's access, with no separate back door.
**What you'll bring** + Hands-on experience with fine-grained security on a cloud data warehouse: row-level and column-level security, masking, authorized views, and IAM. BigQuery is ideal, and Snowflake or Databricks experience also counts. + A solid grounding in data security and governance: role- and attribute-based access control, PII handling, and anonymization / masking.
+ MCP or other LLM tool-use / agent integrations; Looker API or embedding. + BigQuery cost governance. + Collibra policy automation.
+ Collibra policy automation. + Federated query engines (Trino / Starburst). + Experience with FERPA, HIPAA, or other regulated data.
Complete your application on pearson.jobs. The employer’s form will show what is required.
Already applied? Track this application
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.
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.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Virtual, LKA
+ Shape a new team. As an early hire, your patterns become the group's patterns. \#LI-Hybrid **Who we are:**
**Schedule:** FULL\_TIME **Workplace Type:** Hybrid **Req ID:** 26355 \#LI-REMOTE
No clear work-authorization passage found. Eligibility is unconfirmed.