Data Engineer # 4885 at GRAIL
Durham, NC
$86,000–$106,000from the description
Jul 22, 2026
Durham, NC
Jul 23, 2026
What this job asks for AI summary
This role sits at the intersection of data engineering, analytics, and laboratory operations, focused on transforming raw operational and lab data into reliable datasets and dashboards that support high-throughput clinical lab processes. Day-to-day work spans building and maintaining BI dashboards, implementing process monitoring and statistical controls, defining KPIs, and supporting root-cause investigations. It suits an experienced analytics or data engineer comfortable in regulated biotech or life sciences environments.
Mid level · 5+ years · Durham-Chapel Hill, NC · Bachelor's required · Full-time
Advertised as Senior, but the requirements read as Mid.
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 1 people in the Durham-Chapel Hill, NC area plausibly meet what this posting asks for (operations research analysts). range 1–1
Applicant volume Light — Few people clear these requirements, so an application that does clear them gets looked at. Worth applying to even if you miss a nice-to-have.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $111,509 (middle half $80,707–$146,870). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (10)
The role is titled 'Senior' but the required experience floor is 5+ years total and 2–3 years for specific sub-skills, which aligns more closely with a Mid-level practitioner on a normal career ladder. The 'Senior' label appears to reflect internal titling rather than a genuinely senior scope.
SOC classification is a close call: the role blends analytics engineering (pipeline/data modeling → 15-1243) with BI/reporting and process analytics (→ 15-2031). The dominant day-to-day emphasis on dashboards, KPI reporting, SPC, and root-cause analysis tips it toward 15-2031, with 15-1243 as a credible runner-up.
AWS is listed as a hard gate with specific sub-services (Redshift, S3, Glue, Managed Airflow) named as examples; Snowflake is offered as an 'and/or' alternative. The sub-services are captured separately as preferred since they are framed as illustrative examples ('e.g.') within the broader AWS requirement.
The BI platform requirement names Tableau as an example ('e.g., Tableau'); it is treated as a hard gate on the capability, with Tableau as the named tool. No other BI platform is explicitly named as an alternative.
SaaS data source experience (NetSuite, Salesforce, Workday, Coupa) is listed as a required qualification; NetSuite is captured as the primary skill with the others as alternatives since the requirement is for experience with this category of tools.
'data modeling' is retained as a skill here solely to carry the 3-year years demanded figure stated in the required qualifications; it refers to dimensional/semantic modeling experience.
The work arrangement is hybrid (minimum 60% on-site in Durham, NC), not fully remote.
Master's degree is listed under Preferred Qualifications only; the hard requirement is a Bachelor's degree.
Laboratory operations experience (5+ years) and knowledge of clinical lab workflows and QMS frameworks (GMP, ISO 13485, ISO 15189, CLIA, CAP, NYS, FDA) appear under Preferred Qualifications and are not captured as required skills.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): Amazon Managed Workflows for Apache Airflow.
Read the full posting
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